Overview

Brought to you by YData

Dataset statistics

 Full DatasetSystematic Sample
Number of variables7878
Number of observations100000030000
Missing cells00
Missing cells (%)0.0%0.0%
Total size in memory595.1 MiB17.9 MiB
Average record size in memory624.0 B624.0 B

Variable types

 Full DatasetSystematic Sample
Numeric4040
Text3838

Alerts

Full DatasetSystematic Sample
customer_id has unique values customer_id has unique values Unique
membership_years has 99846 (10.0%) zeros membership_years has 3047 (10.2%) zeros Zeros
number_of_children has 199753 (20.0%) zeros number_of_children has 6001 (20.0%) zeros Zeros
transaction_hour has 41756 (4.2%) zeros transaction_hour has 1312 (4.4%) zeros Zeros
avg_discount_used has 10010 (1.0%) zeros Alert not present in this datasetZeros
in_store_purchases has 10016 (1.0%) zeros in_store_purchases has 317 (1.1%) zeros Zeros
total_returned_items has 100060 (10.0%) zeros total_returned_items has 3043 (10.1%) zeros Zeros
product_stock has 10174 (1.0%) zeros Alert not present in this datasetZeros
customer_support_calls has 49755 (5.0%) zeros customer_support_calls has 1560 (5.2%) zeros Zeros
website_visits has 10111 (1.0%) zeros Alert not present in this datasetZeros
Alert not present in this datasetdiscount_applied has 317 (1.1%) zeros Zeros
Alert not present in this datasetproduct_return_rate has 315 (1.1%) zeros Zeros

Reproduction

 Full DatasetSystematic Sample
Analysis started2025-06-06 02:05:49.1724632025-06-06 02:07:41.655463
Analysis finished2025-06-06 02:07:41.6300502025-06-06 02:07:45.980651
Duration1 minute and 52.46 seconds4.33 seconds
Software versionydata-profiling vv4.16.1ydata-profiling vv4.16.1
Download configurationconfig.jsonconfig.json

Variables

customer_id
Real number (ℝ)

 Full DatasetSystematic Sample
Distinct100000030000
Distinct (%)100.0%100.0%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean500000.5494984.5
 Full DatasetSystematic Sample
Minimum11
Maximum1000000989968
Zeros00
Zeros (%)0.0%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T02:07:46.698091image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Full DatasetSystematic Sample
Minimum11
5-th percentile50000.9549499.35
Q1250000.75247492.75
median500000.5494984.5
Q3750000.25742476.25
95-th percentile950000.05940469.65
Maximum1000000989968
Range999999989967
Interquartile range (IQR)499999.5494983.5

Descriptive statistics

 Full DatasetSystematic Sample
Standard deviation288675.2789285793.1463
Coefficient of variation (CV)0.57734998050.5773779711
Kurtosis-1.2-1.2
Mean500000.5494984.5
Median Absolute Deviation (MAD)250000247500
Skewness-2.511790261 × 10-150
Sum5.000005 × 10111.4849535 × 1010
Variance8.333341667 × 10108.16777225 × 1010
MonotonicityStrictly increasingStrictly increasing
2025-06-06T02:07:47.026693image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
999984 1
 
< 0.1%
999983 1
 
< 0.1%
999982 1
 
< 0.1%
999981 1
 
< 0.1%
999980 1
 
< 0.1%
999979 1
 
< 0.1%
999978 1
 
< 0.1%
999977 1
 
< 0.1%
999976 1
 
< 0.1%
999975 1
 
< 0.1%
Other values (999990) 999990
> 99.9%
ValueCountFrequency (%)
989440 1
 
< 0.1%
989407 1
 
< 0.1%
989374 1
 
< 0.1%
989341 1
 
< 0.1%
989308 1
 
< 0.1%
989275 1
 
< 0.1%
989242 1
 
< 0.1%
989209 1
 
< 0.1%
989176 1
 
< 0.1%
989143 1
 
< 0.1%
Other values (29990) 29990
> 99.9%
ValueCountFrequency (%)
1 1
< 0.1%
2 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
5 1
< 0.1%
ValueCountFrequency (%)
1 1
< 0.1%
34 1
< 0.1%
67 1
< 0.1%
100 1
< 0.1%
133 1
< 0.1%
ValueCountFrequency (%)
1 1
< 0.1%
34 1
< 0.1%
67 1
< 0.1%
100 1
< 0.1%
133 1
< 0.1%
ValueCountFrequency (%)
1 1
< 0.1%
2 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
5 1
< 0.1%

age
Real number (ℝ)

 Full DatasetSystematic Sample
Distinct6262
Distinct (%)< 0.1%0.2%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean48.49660548.61583333
 Full DatasetSystematic Sample
Minimum1818
Maximum7979
Zeros00
Zeros (%)0.0%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T02:07:47.340760image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Full DatasetSystematic Sample
Minimum1818
5-th percentile2121
Q13333
median4949
Q36464
95-th percentile7676
Maximum7979
Range6161
Interquartile range (IQR)3131

Descriptive statistics

 Full DatasetSystematic Sample
Standard deviation17.8743811617.81809657
Coefficient of variation (CV)0.36856974140.3665080973
Kurtosis-1.198117884-1.189797483
Mean48.49660548.61583333
Median Absolute Deviation (MAD)1515
Skewness-0.0002769945754-0.005388281958
Sum484966051458475
Variance319.493502317.4845655
MonotonicityNot monotonicNot monotonic
2025-06-06T02:07:47.653890image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
53 16423
 
1.6%
54 16412
 
1.6%
33 16407
 
1.6%
36 16363
 
1.6%
62 16324
 
1.6%
39 16290
 
1.6%
34 16284
 
1.6%
40 16274
 
1.6%
32 16264
 
1.6%
19 16248
 
1.6%
Other values (52) 836711
83.7%
ValueCountFrequency (%)
47 532
 
1.8%
37 524
 
1.7%
42 520
 
1.7%
32 519
 
1.7%
79 517
 
1.7%
61 516
 
1.7%
53 516
 
1.7%
68 508
 
1.7%
33 507
 
1.7%
40 506
 
1.7%
Other values (52) 24835
82.8%
ValueCountFrequency (%)
18 16003
1.6%
19 16248
1.6%
20 16116
1.6%
21 16016
1.6%
22 16211
1.6%
ValueCountFrequency (%)
18 479
1.6%
19 484
1.6%
20 462
1.5%
21 467
1.6%
22 461
1.5%
ValueCountFrequency (%)
18 479
< 0.1%
19 484
< 0.1%
20 462
< 0.1%
21 467
< 0.1%
22 461
< 0.1%
ValueCountFrequency (%)
18 16003
53.3%
19 16248
54.2%
20 16116
53.7%
21 16016
53.4%
22 16211
54.0%

gender
['Text', 'Text']

 Full DatasetSystematic Sample
Distinct33
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T02:07:48.010783image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

 Full DatasetSystematic Sample
Max length66
Median length55
Mean length5.0011745.0023
Min length44

Characters and Unicode

 Full DatasetSystematic Sample
Total characters5001174150069
Distinct characters1010
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Full DatasetSystematic Sample
Unique00 ?
Unique (%)0.0%0.0%

Sample

 Full DatasetSystematic Sample
1st rowOtherOther
2nd rowFemaleFemale
3rd rowFemaleOther
4th rowFemaleMale
5th rowFemaleMale
ValueCountFrequency (%)
other 333734
33.4%
female 333720
33.4%
male 332546
33.3%
ValueCountFrequency (%)
other 10119
33.7%
female 9975
33.2%
male 9906
33.0%
2025-06-06T02:07:48.492922image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 1333720
26.7%
a 666266
13.3%
l 666266
13.3%
O 333734
 
6.7%
t 333734
 
6.7%
h 333734
 
6.7%
r 333734
 
6.7%
F 333720
 
6.7%
m 333720
 
6.7%
M 332546
 
6.6%
ValueCountFrequency (%)
e 39975
26.6%
a 19881
13.2%
l 19881
13.2%
O 10119
 
6.7%
t 10119
 
6.7%
h 10119
 
6.7%
r 10119
 
6.7%
F 9975
 
6.6%
m 9975
 
6.6%
M 9906
 
6.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 5001174
100.0%
ValueCountFrequency (%)
(unknown) 150069
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 1333720
26.7%
a 666266
13.3%
l 666266
13.3%
O 333734
 
6.7%
t 333734
 
6.7%
h 333734
 
6.7%
r 333734
 
6.7%
F 333720
 
6.7%
m 333720
 
6.7%
M 332546
 
6.6%
ValueCountFrequency (%)
e 39975
26.6%
a 19881
13.2%
l 19881
13.2%
O 10119
 
6.7%
t 10119
 
6.7%
h 10119
 
6.7%
r 10119
 
6.7%
F 9975
 
6.6%
m 9975
 
6.6%
M 9906
 
6.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 5001174
100.0%
ValueCountFrequency (%)
(unknown) 150069
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 1333720
26.7%
a 666266
13.3%
l 666266
13.3%
O 333734
 
6.7%
t 333734
 
6.7%
h 333734
 
6.7%
r 333734
 
6.7%
F 333720
 
6.7%
m 333720
 
6.7%
M 332546
 
6.6%
ValueCountFrequency (%)
e 39975
26.6%
a 19881
13.2%
l 19881
13.2%
O 10119
 
6.7%
t 10119
 
6.7%
h 10119
 
6.7%
r 10119
 
6.7%
F 9975
 
6.6%
m 9975
 
6.6%
M 9906
 
6.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 5001174
100.0%
ValueCountFrequency (%)
(unknown) 150069
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 1333720
26.7%
a 666266
13.3%
l 666266
13.3%
O 333734
 
6.7%
t 333734
 
6.7%
h 333734
 
6.7%
r 333734
 
6.7%
F 333720
 
6.7%
m 333720
 
6.7%
M 332546
 
6.6%
ValueCountFrequency (%)
e 39975
26.6%
a 19881
13.2%
l 19881
13.2%
O 10119
 
6.7%
t 10119
 
6.7%
h 10119
 
6.7%
r 10119
 
6.7%
F 9975
 
6.6%
m 9975
 
6.6%
M 9906
 
6.6%

income_bracket
['Text', 'Text']

 Full DatasetSystematic Sample
Distinct33
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T02:07:48.798377image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

 Full DatasetSystematic Sample
Max length66
Median length44
Mean length4.3337134.335333333
Min length33

Characters and Unicode

 Full DatasetSystematic Sample
Total characters4333713130060
Distinct characters1212
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Full DatasetSystematic Sample
Unique00 ?
Unique (%)0.0%0.0%

Sample

 Full DatasetSystematic Sample
1st rowHighHigh
2nd rowMediumHigh
3rd rowLowHigh
4th rowLowLow
5th rowLowLow
ValueCountFrequency (%)
high 333612
33.4%
medium 333367
33.3%
low 333021
33.3%
ValueCountFrequency (%)
high 10060
33.5%
medium 10000
33.3%
low 9940
33.1%
2025-06-06T02:07:49.329559image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i 666979
15.4%
H 333612
7.7%
g 333612
7.7%
h 333612
7.7%
M 333367
7.7%
e 333367
7.7%
d 333367
7.7%
u 333367
7.7%
m 333367
7.7%
L 333021
7.7%
Other values (2) 666042
15.4%
ValueCountFrequency (%)
i 20060
15.4%
H 10060
7.7%
g 10060
7.7%
h 10060
7.7%
M 10000
7.7%
e 10000
7.7%
d 10000
7.7%
u 10000
7.7%
m 10000
7.7%
L 9940
7.6%
Other values (2) 19880
15.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4333713
100.0%
ValueCountFrequency (%)
(unknown) 130060
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
i 666979
15.4%
H 333612
7.7%
g 333612
7.7%
h 333612
7.7%
M 333367
7.7%
e 333367
7.7%
d 333367
7.7%
u 333367
7.7%
m 333367
7.7%
L 333021
7.7%
Other values (2) 666042
15.4%
ValueCountFrequency (%)
i 20060
15.4%
H 10060
7.7%
g 10060
7.7%
h 10060
7.7%
M 10000
7.7%
e 10000
7.7%
d 10000
7.7%
u 10000
7.7%
m 10000
7.7%
L 9940
7.6%
Other values (2) 19880
15.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4333713
100.0%
ValueCountFrequency (%)
(unknown) 130060
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
i 666979
15.4%
H 333612
7.7%
g 333612
7.7%
h 333612
7.7%
M 333367
7.7%
e 333367
7.7%
d 333367
7.7%
u 333367
7.7%
m 333367
7.7%
L 333021
7.7%
Other values (2) 666042
15.4%
ValueCountFrequency (%)
i 20060
15.4%
H 10060
7.7%
g 10060
7.7%
h 10060
7.7%
M 10000
7.7%
e 10000
7.7%
d 10000
7.7%
u 10000
7.7%
m 10000
7.7%
L 9940
7.6%
Other values (2) 19880
15.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4333713
100.0%
ValueCountFrequency (%)
(unknown) 130060
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
i 666979
15.4%
H 333612
7.7%
g 333612
7.7%
h 333612
7.7%
M 333367
7.7%
e 333367
7.7%
d 333367
7.7%
u 333367
7.7%
m 333367
7.7%
L 333021
7.7%
Other values (2) 666042
15.4%
ValueCountFrequency (%)
i 20060
15.4%
H 10060
7.7%
g 10060
7.7%
h 10060
7.7%
M 10000
7.7%
e 10000
7.7%
d 10000
7.7%
u 10000
7.7%
m 10000
7.7%
L 9940
7.6%
Other values (2) 19880
15.3%

loyalty_program
['Text', 'Text']

 Full DatasetSystematic Sample
Distinct22
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T02:07:49.482942image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

 Full DatasetSystematic Sample
Max length33
Median length22
Mean length2.4997122.498133333
Min length22

Characters and Unicode

 Full DatasetSystematic Sample
Total characters249971274944
Distinct characters55
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Full DatasetSystematic Sample
Unique00 ?
Unique (%)0.0%0.0%

Sample

 Full DatasetSystematic Sample
1st rowNoNo
2nd rowNoYes
3rd rowNoYes
4th rowNoYes
5th rowYesYes
ValueCountFrequency (%)
no 500288
50.0%
yes 499712
50.0%
ValueCountFrequency (%)
no 15056
50.2%
yes 14944
49.8%
2025-06-06T02:07:49.759327image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 500288
20.0%
o 500288
20.0%
Y 499712
20.0%
e 499712
20.0%
s 499712
20.0%
ValueCountFrequency (%)
N 15056
20.1%
o 15056
20.1%
Y 14944
19.9%
e 14944
19.9%
s 14944
19.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2499712
100.0%
ValueCountFrequency (%)
(unknown) 74944
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
N 500288
20.0%
o 500288
20.0%
Y 499712
20.0%
e 499712
20.0%
s 499712
20.0%
ValueCountFrequency (%)
N 15056
20.1%
o 15056
20.1%
Y 14944
19.9%
e 14944
19.9%
s 14944
19.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2499712
100.0%
ValueCountFrequency (%)
(unknown) 74944
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
N 500288
20.0%
o 500288
20.0%
Y 499712
20.0%
e 499712
20.0%
s 499712
20.0%
ValueCountFrequency (%)
N 15056
20.1%
o 15056
20.1%
Y 14944
19.9%
e 14944
19.9%
s 14944
19.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2499712
100.0%
ValueCountFrequency (%)
(unknown) 74944
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
N 500288
20.0%
o 500288
20.0%
Y 499712
20.0%
e 499712
20.0%
s 499712
20.0%
ValueCountFrequency (%)
N 15056
20.1%
o 15056
20.1%
Y 14944
19.9%
e 14944
19.9%
s 14944
19.9%

membership_years
Real number (ℝ)

 Full DatasetSystematic Sample
Distinct1010
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean4.4974534.486833333
 Full DatasetSystematic Sample
Minimum00
Maximum99
Zeros998463047
Zeros (%)10.0%10.2%
Negative00
Negative (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T02:07:49.855829image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Full DatasetSystematic Sample
Minimum00
5-th percentile00
Q122
median44
Q377
95-th percentile99
Maximum99
Range99
Interquartile range (IQR)55

Descriptive statistics

 Full DatasetSystematic Sample
Standard deviation2.8724055712.872809613
Coefficient of variation (CV)0.63867383850.640275535
Kurtosis-1.22454665-1.214547006
Mean4.4974534.486833333
Median Absolute Deviation (MAD)32
Skewness0.0015904633240.007875075606
Sum4497453134605
Variance8.2507137648.253035073
MonotonicityNot monotonicNot monotonic
2025-06-06T02:07:49.958290image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
1 100686
10.1%
5 100183
10.0%
4 100137
10.0%
9 99977
10.0%
2 99964
10.0%
8 99891
10.0%
6 99865
10.0%
0 99846
10.0%
7 99728
10.0%
3 99723
10.0%
ValueCountFrequency (%)
9 3065
10.2%
5 3057
10.2%
0 3047
10.2%
4 3044
10.1%
6 3042
10.1%
1 2991
10.0%
2 2986
10.0%
3 2977
9.9%
7 2915
9.7%
8 2876
9.6%
ValueCountFrequency (%)
0 99846
10.0%
1 100686
10.1%
2 99964
10.0%
3 99723
10.0%
4 100137
10.0%
ValueCountFrequency (%)
0 3047
10.2%
1 2991
10.0%
2 2986
10.0%
3 2977
9.9%
4 3044
10.1%
ValueCountFrequency (%)
0 3047
0.3%
1 2991
0.3%
2 2986
0.3%
3 2977
0.3%
4 3044
0.3%
ValueCountFrequency (%)
0 99846
332.8%
1 100686
335.6%
2 99964
333.2%
3 99723
332.4%
4 100137
333.8%

churned
['Text', 'Text']

 Full DatasetSystematic Sample
Distinct22
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T02:07:50.114604image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

 Full DatasetSystematic Sample
Max length33
Median length22
Mean length2.4997292.4964
Min length22

Characters and Unicode

 Full DatasetSystematic Sample
Total characters249972974892
Distinct characters55
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Full DatasetSystematic Sample
Unique00 ?
Unique (%)0.0%0.0%

Sample

 Full DatasetSystematic Sample
1st rowNoNo
2nd rowNoYes
3rd rowNoYes
4th rowNoYes
5th rowYesNo
ValueCountFrequency (%)
no 500271
50.0%
yes 499729
50.0%
ValueCountFrequency (%)
no 15108
50.4%
yes 14892
49.6%
2025-06-06T02:07:50.645965image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 500271
20.0%
o 500271
20.0%
Y 499729
20.0%
e 499729
20.0%
s 499729
20.0%
ValueCountFrequency (%)
N 15108
20.2%
o 15108
20.2%
Y 14892
19.9%
e 14892
19.9%
s 14892
19.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2499729
100.0%
ValueCountFrequency (%)
(unknown) 74892
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
N 500271
20.0%
o 500271
20.0%
Y 499729
20.0%
e 499729
20.0%
s 499729
20.0%
ValueCountFrequency (%)
N 15108
20.2%
o 15108
20.2%
Y 14892
19.9%
e 14892
19.9%
s 14892
19.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2499729
100.0%
ValueCountFrequency (%)
(unknown) 74892
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
N 500271
20.0%
o 500271
20.0%
Y 499729
20.0%
e 499729
20.0%
s 499729
20.0%
ValueCountFrequency (%)
N 15108
20.2%
o 15108
20.2%
Y 14892
19.9%
e 14892
19.9%
s 14892
19.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2499729
100.0%
ValueCountFrequency (%)
(unknown) 74892
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
N 500271
20.0%
o 500271
20.0%
Y 499729
20.0%
e 499729
20.0%
s 499729
20.0%
ValueCountFrequency (%)
N 15108
20.2%
o 15108
20.2%
Y 14892
19.9%
e 14892
19.9%
s 14892
19.9%

marital_status
['Text', 'Text']

 Full DatasetSystematic Sample
Distinct33
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T02:07:50.840777image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

 Full DatasetSystematic Sample
Max length88
Median length77
Mean length7.0008667.0019
Min length66

Characters and Unicode

 Full DatasetSystematic Sample
Total characters7000866210057
Distinct characters1414
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Full DatasetSystematic Sample
Unique00 ?
Unique (%)0.0%0.0%

Sample

 Full DatasetSystematic Sample
1st rowDivorcedDivorced
2nd rowMarriedDivorced
3rd rowMarriedMarried
4th rowDivorcedMarried
5th rowDivorcedSingle
ValueCountFrequency (%)
divorced 333816
33.4%
married 333234
33.3%
single 332950
33.3%
ValueCountFrequency (%)
married 10085
33.6%
divorced 9986
33.3%
single 9929
33.1%
2025-06-06T02:07:51.163917image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
r 1000284
14.3%
i 1000000
14.3%
e 1000000
14.3%
d 667050
9.5%
D 333816
 
4.8%
v 333816
 
4.8%
c 333816
 
4.8%
o 333816
 
4.8%
M 333234
 
4.8%
a 333234
 
4.8%
Other values (4) 1331800
19.0%
ValueCountFrequency (%)
r 30156
14.4%
i 30000
14.3%
e 30000
14.3%
d 20071
9.6%
a 10085
 
4.8%
M 10085
 
4.8%
D 9986
 
4.8%
v 9986
 
4.8%
o 9986
 
4.8%
c 9986
 
4.8%
Other values (4) 39716
18.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 7000866
100.0%
ValueCountFrequency (%)
(unknown) 210057
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
r 1000284
14.3%
i 1000000
14.3%
e 1000000
14.3%
d 667050
9.5%
D 333816
 
4.8%
v 333816
 
4.8%
c 333816
 
4.8%
o 333816
 
4.8%
M 333234
 
4.8%
a 333234
 
4.8%
Other values (4) 1331800
19.0%
ValueCountFrequency (%)
r 30156
14.4%
i 30000
14.3%
e 30000
14.3%
d 20071
9.6%
a 10085
 
4.8%
M 10085
 
4.8%
D 9986
 
4.8%
v 9986
 
4.8%
o 9986
 
4.8%
c 9986
 
4.8%
Other values (4) 39716
18.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 7000866
100.0%
ValueCountFrequency (%)
(unknown) 210057
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
r 1000284
14.3%
i 1000000
14.3%
e 1000000
14.3%
d 667050
9.5%
D 333816
 
4.8%
v 333816
 
4.8%
c 333816
 
4.8%
o 333816
 
4.8%
M 333234
 
4.8%
a 333234
 
4.8%
Other values (4) 1331800
19.0%
ValueCountFrequency (%)
r 30156
14.4%
i 30000
14.3%
e 30000
14.3%
d 20071
9.6%
a 10085
 
4.8%
M 10085
 
4.8%
D 9986
 
4.8%
v 9986
 
4.8%
o 9986
 
4.8%
c 9986
 
4.8%
Other values (4) 39716
18.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 7000866
100.0%
ValueCountFrequency (%)
(unknown) 210057
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
r 1000284
14.3%
i 1000000
14.3%
e 1000000
14.3%
d 667050
9.5%
D 333816
 
4.8%
v 333816
 
4.8%
c 333816
 
4.8%
o 333816
 
4.8%
M 333234
 
4.8%
a 333234
 
4.8%
Other values (4) 1331800
19.0%
ValueCountFrequency (%)
r 30156
14.4%
i 30000
14.3%
e 30000
14.3%
d 20071
9.6%
a 10085
 
4.8%
M 10085
 
4.8%
D 9986
 
4.8%
v 9986
 
4.8%
o 9986
 
4.8%
c 9986
 
4.8%
Other values (4) 39716
18.9%

number_of_children
Real number (ℝ)

 Full DatasetSystematic Sample
Distinct55
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean2.0005542.0023
 Full DatasetSystematic Sample
Minimum00
Maximum44
Zeros1997536001
Zeros (%)20.0%20.0%
Negative00
Negative (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T02:07:51.264543image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Full DatasetSystematic Sample
Minimum00
5-th percentile00
Q111
median22
Q333
95-th percentile44
Maximum44
Range44
Interquartile range (IQR)22

Descriptive statistics

 Full DatasetSystematic Sample
Standard deviation1.4142141611.4163668
Coefficient of variation (CV)0.70691126610.7073699248
Kurtosis-1.300270709-1.302969252
Mean2.0005542.0023
Median Absolute Deviation (MAD)11
Skewness-0.0001223295646-0.0001202378719
Sum200055460069
Variance2.0000016932.006094913
MonotonicityNot monotonicNot monotonic
2025-06-06T02:07:51.370848image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%)
1 200307
20.0%
4 200157
20.0%
3 200053
20.0%
0 199753
20.0%
2 199730
20.0%
ValueCountFrequency (%)
4 6057
20.2%
0 6001
20.0%
1 5996
20.0%
2 5993
20.0%
3 5953
19.8%
ValueCountFrequency (%)
0 199753
20.0%
1 200307
20.0%
2 199730
20.0%
3 200053
20.0%
4 200157
20.0%
ValueCountFrequency (%)
0 6001
20.0%
1 5996
20.0%
2 5993
20.0%
3 5953
19.8%
4 6057
20.2%
ValueCountFrequency (%)
0 6001
0.6%
1 5996
0.6%
2 5993
0.6%
3 5953
0.6%
4 6057
0.6%
ValueCountFrequency (%)
0 199753
665.8%
1 200307
667.7%
2 199730
665.8%
3 200053
666.8%
4 200157
667.2%

education_level
['Text', 'Text']

 Full DatasetSystematic Sample
Distinct44
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T02:07:51.596900image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

 Full DatasetSystematic Sample
Max length1111
Median length1010
Mean length8.000648.0221
Min length33

Characters and Unicode

 Full DatasetSystematic Sample
Total characters8000640240663
Distinct characters1919
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Full DatasetSystematic Sample
Unique00 ?
Unique (%)0.0%0.0%

Sample

 Full DatasetSystematic Sample
1st rowBachelor'sBachelor's
2nd rowPhDMaster's
3rd rowBachelor'sPhD
4th rowMaster'sHigh School
5th rowBachelor'sPhD
ValueCountFrequency (%)
bachelor's 250360
20.0%
high 250105
20.0%
school 250105
20.0%
phd 250079
20.0%
master's 249456
20.0%
ValueCountFrequency (%)
bachelor's 7633
20.4%
master's 7504
20.0%
high 7464
19.9%
school 7464
19.9%
phd 7399
19.7%
2025-06-06T02:07:51.944170image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
h 1000649
12.5%
o 750570
 
9.4%
s 749272
 
9.4%
c 500465
 
6.3%
l 500465
 
6.3%
e 499816
 
6.2%
a 499816
 
6.2%
' 499816
 
6.2%
r 499816
 
6.2%
B 250360
 
3.1%
Other values (9) 2249595
28.1%
ValueCountFrequency (%)
h 29960
12.4%
s 22641
 
9.4%
o 22561
 
9.4%
' 15137
 
6.3%
r 15137
 
6.3%
a 15137
 
6.3%
e 15137
 
6.3%
l 15097
 
6.3%
c 15097
 
6.3%
B 7633
 
3.2%
Other values (9) 67126
27.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 8000640
100.0%
ValueCountFrequency (%)
(unknown) 240663
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
h 1000649
12.5%
o 750570
 
9.4%
s 749272
 
9.4%
c 500465
 
6.3%
l 500465
 
6.3%
e 499816
 
6.2%
a 499816
 
6.2%
' 499816
 
6.2%
r 499816
 
6.2%
B 250360
 
3.1%
Other values (9) 2249595
28.1%
ValueCountFrequency (%)
h 29960
12.4%
s 22641
 
9.4%
o 22561
 
9.4%
' 15137
 
6.3%
r 15137
 
6.3%
a 15137
 
6.3%
e 15137
 
6.3%
l 15097
 
6.3%
c 15097
 
6.3%
B 7633
 
3.2%
Other values (9) 67126
27.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 8000640
100.0%
ValueCountFrequency (%)
(unknown) 240663
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
h 1000649
12.5%
o 750570
 
9.4%
s 749272
 
9.4%
c 500465
 
6.3%
l 500465
 
6.3%
e 499816
 
6.2%
a 499816
 
6.2%
' 499816
 
6.2%
r 499816
 
6.2%
B 250360
 
3.1%
Other values (9) 2249595
28.1%
ValueCountFrequency (%)
h 29960
12.4%
s 22641
 
9.4%
o 22561
 
9.4%
' 15137
 
6.3%
r 15137
 
6.3%
a 15137
 
6.3%
e 15137
 
6.3%
l 15097
 
6.3%
c 15097
 
6.3%
B 7633
 
3.2%
Other values (9) 67126
27.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 8000640
100.0%
ValueCountFrequency (%)
(unknown) 240663
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
h 1000649
12.5%
o 750570
 
9.4%
s 749272
 
9.4%
c 500465
 
6.3%
l 500465
 
6.3%
e 499816
 
6.2%
a 499816
 
6.2%
' 499816
 
6.2%
r 499816
 
6.2%
B 250360
 
3.1%
Other values (9) 2249595
28.1%
ValueCountFrequency (%)
h 29960
12.4%
s 22641
 
9.4%
o 22561
 
9.4%
' 15137
 
6.3%
r 15137
 
6.3%
a 15137
 
6.3%
e 15137
 
6.3%
l 15097
 
6.3%
c 15097
 
6.3%
B 7633
 
3.2%
Other values (9) 67126
27.9%

occupation
['Text', 'Text']

 Full DatasetSystematic Sample
Distinct44
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T02:07:52.161833image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

 Full DatasetSystematic Sample
Max length1313
Median length1010
Mean length9.5008549.512833333
Min length77

Characters and Unicode

 Full DatasetSystematic Sample
Total characters9500854285385
Distinct characters1717
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Full DatasetSystematic Sample
Unique00 ?
Unique (%)0.0%0.0%

Sample

 Full DatasetSystematic Sample
1st rowSelf-EmployedSelf-Employed
2nd rowUnemployedUnemployed
3rd rowSelf-EmployedEmployed
4th rowEmployedUnemployed
5th rowEmployedEmployed
ValueCountFrequency (%)
employed 250857
25.1%
unemployed 250117
25.0%
self-employed 249941
25.0%
retired 249085
24.9%
ValueCountFrequency (%)
self-employed 7629
25.4%
employed 7552
25.2%
retired 7466
24.9%
unemployed 7353
24.5%
2025-06-06T02:07:52.527969image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 1749143
18.4%
l 1000856
10.5%
d 1000000
10.5%
o 750915
7.9%
m 750915
7.9%
y 750915
7.9%
p 750915
7.9%
E 500798
 
5.3%
U 250117
 
2.6%
n 250117
 
2.6%
Other values (7) 1746163
18.4%
ValueCountFrequency (%)
e 52448
18.4%
l 30163
10.6%
d 30000
10.5%
o 22534
7.9%
p 22534
7.9%
y 22534
7.9%
m 22534
7.9%
E 15181
 
5.3%
S 7629
 
2.7%
f 7629
 
2.7%
Other values (7) 52199
18.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 9500854
100.0%
ValueCountFrequency (%)
(unknown) 285385
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 1749143
18.4%
l 1000856
10.5%
d 1000000
10.5%
o 750915
7.9%
m 750915
7.9%
y 750915
7.9%
p 750915
7.9%
E 500798
 
5.3%
U 250117
 
2.6%
n 250117
 
2.6%
Other values (7) 1746163
18.4%
ValueCountFrequency (%)
e 52448
18.4%
l 30163
10.6%
d 30000
10.5%
o 22534
7.9%
p 22534
7.9%
y 22534
7.9%
m 22534
7.9%
E 15181
 
5.3%
S 7629
 
2.7%
f 7629
 
2.7%
Other values (7) 52199
18.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 9500854
100.0%
ValueCountFrequency (%)
(unknown) 285385
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 1749143
18.4%
l 1000856
10.5%
d 1000000
10.5%
o 750915
7.9%
m 750915
7.9%
y 750915
7.9%
p 750915
7.9%
E 500798
 
5.3%
U 250117
 
2.6%
n 250117
 
2.6%
Other values (7) 1746163
18.4%
ValueCountFrequency (%)
e 52448
18.4%
l 30163
10.6%
d 30000
10.5%
o 22534
7.9%
p 22534
7.9%
y 22534
7.9%
m 22534
7.9%
E 15181
 
5.3%
S 7629
 
2.7%
f 7629
 
2.7%
Other values (7) 52199
18.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 9500854
100.0%
ValueCountFrequency (%)
(unknown) 285385
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 1749143
18.4%
l 1000856
10.5%
d 1000000
10.5%
o 750915
7.9%
m 750915
7.9%
y 750915
7.9%
p 750915
7.9%
E 500798
 
5.3%
U 250117
 
2.6%
n 250117
 
2.6%
Other values (7) 1746163
18.4%
ValueCountFrequency (%)
e 52448
18.4%
l 30163
10.6%
d 30000
10.5%
o 22534
7.9%
p 22534
7.9%
y 22534
7.9%
m 22534
7.9%
E 15181
 
5.3%
S 7629
 
2.7%
f 7629
 
2.7%
Other values (7) 52199
18.3%

transaction_id
Real number (ℝ)

 Full DatasetSystematic Sample
Distinct63257629558
Distinct (%)63.3%98.5%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean499891.7314501922.5861
 Full DatasetSystematic Sample
Minimum231
Maximum999999999999
Zeros00
Zeros (%)0.0%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T02:07:52.747100image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Full DatasetSystematic Sample
Minimum231
5-th percentile50200.9550175.45
Q1249878.75250889.75
median499559.5502763.5
Q3750071.25752751.25
95-th percentile950045.2950656.2
Maximum999999999999
Range999997999968
Interquartile range (IQR)500192.5501861.5

Descriptive statistics

 Full DatasetSystematic Sample
Standard deviation288706.0577289037.1838
Coefficient of variation (CV)0.57753717350.5758600865
Kurtosis-1.200114605-1.203309752
Mean499891.7314501922.5861
Median Absolute Deviation (MAD)250088.5250939
Skewness0.002395187253-0.008982096119
Sum4.998917314 × 10111.505767758 × 1010
Variance8.335118772 × 10108.354249365 × 1010
MonotonicityNot monotonicNot monotonic
2025-06-06T02:07:52.965042image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
115913 9
 
< 0.1%
504562 8
 
< 0.1%
344167 8
 
< 0.1%
2773 8
 
< 0.1%
239407 8
 
< 0.1%
620816 8
 
< 0.1%
273197 8
 
< 0.1%
254678 7
 
< 0.1%
798940 7
 
< 0.1%
335691 7
 
< 0.1%
Other values (632566) 999922
> 99.9%
ValueCountFrequency (%)
295619 3
 
< 0.1%
875137 3
 
< 0.1%
101418 3
 
< 0.1%
620816 3
 
< 0.1%
44700 3
 
< 0.1%
288436 3
 
< 0.1%
258166 3
 
< 0.1%
257013 2
 
< 0.1%
784191 2
 
< 0.1%
495427 2
 
< 0.1%
Other values (29548) 29973
99.9%
ValueCountFrequency (%)
2 2
< 0.1%
3 1
 
< 0.1%
5 3
< 0.1%
6 1
 
< 0.1%
7 2
< 0.1%
ValueCountFrequency (%)
31 1
< 0.1%
67 1
< 0.1%
111 1
< 0.1%
187 1
< 0.1%
214 1
< 0.1%
ValueCountFrequency (%)
31 1
< 0.1%
67 1
< 0.1%
111 1
< 0.1%
187 1
< 0.1%
214 1
< 0.1%
ValueCountFrequency (%)
2 2
< 0.1%
3 1
 
< 0.1%
5 3
< 0.1%
6 1
 
< 0.1%
7 2
< 0.1%

transaction_date
['Text', 'Text']

 Full DatasetSystematic Sample
Distinct99223129990
Distinct (%)99.2%> 99.9%
Missing00
Missing (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T02:07:53.679528image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

 Full DatasetSystematic Sample
Max length1919
Median length1919
Mean length1919
Min length1919

Characters and Unicode

 Full DatasetSystematic Sample
Total characters19000000570000
Distinct characters1313
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Full DatasetSystematic Sample
Unique98450429980 ?
Unique (%)98.5%99.9%

Sample

 Full DatasetSystematic Sample
1st row2020-10-11 10:08:522020-10-11 10:08:52
2nd row2021-12-08 01:07:402020-05-08 05:45:31
3rd row2020-02-17 09:40:482021-01-06 13:38:44
4th row2020-08-13 00:43:142021-04-22 18:40:10
5th row2021-07-02 11:59:032020-04-04 04:51:10
ValueCountFrequency (%)
2020-10-05 1509
 
0.1%
2020-09-06 1467
 
0.1%
2020-10-04 1464
 
0.1%
2020-07-26 1463
 
0.1%
2020-02-26 1458
 
0.1%
2020-05-03 1455
 
0.1%
2021-02-27 1453
 
0.1%
2021-07-30 1451
 
0.1%
2020-09-07 1451
 
0.1%
2020-10-09 1447
 
0.1%
Other values (87119) 1985382
99.3%
ValueCountFrequency (%)
2020-10-23 60
 
0.1%
2020-09-16 57
 
0.1%
2021-03-12 57
 
0.1%
2020-12-22 57
 
0.1%
2021-08-18 57
 
0.1%
2020-02-06 55
 
0.1%
2021-04-26 55
 
0.1%
2020-04-22 55
 
0.1%
2021-08-13 55
 
0.1%
2020-08-01 55
 
0.1%
Other values (26116) 59437
99.1%
2025-06-06T02:07:54.460414image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3798683
20.0%
2 3414072
18.0%
1 2439659
12.8%
: 2000000
10.5%
- 2000000
10.5%
1000000
 
5.3%
3 890067
 
4.7%
5 800311
 
4.2%
4 798703
 
4.2%
7 467556
 
2.5%
Other values (3) 1390949
 
7.3%
ValueCountFrequency (%)
0 114027
20.0%
2 102499
18.0%
1 73048
12.8%
- 60000
10.5%
: 60000
10.5%
30000
 
5.3%
3 26567
 
4.7%
5 23954
 
4.2%
4 23933
 
4.2%
8 14066
 
2.5%
Other values (3) 41906
 
7.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 19000000
100.0%
ValueCountFrequency (%)
(unknown) 570000
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 3798683
20.0%
2 3414072
18.0%
1 2439659
12.8%
: 2000000
10.5%
- 2000000
10.5%
1000000
 
5.3%
3 890067
 
4.7%
5 800311
 
4.2%
4 798703
 
4.2%
7 467556
 
2.5%
Other values (3) 1390949
 
7.3%
ValueCountFrequency (%)
0 114027
20.0%
2 102499
18.0%
1 73048
12.8%
- 60000
10.5%
: 60000
10.5%
30000
 
5.3%
3 26567
 
4.7%
5 23954
 
4.2%
4 23933
 
4.2%
8 14066
 
2.5%
Other values (3) 41906
 
7.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 19000000
100.0%
ValueCountFrequency (%)
(unknown) 570000
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 3798683
20.0%
2 3414072
18.0%
1 2439659
12.8%
: 2000000
10.5%
- 2000000
10.5%
1000000
 
5.3%
3 890067
 
4.7%
5 800311
 
4.2%
4 798703
 
4.2%
7 467556
 
2.5%
Other values (3) 1390949
 
7.3%
ValueCountFrequency (%)
0 114027
20.0%
2 102499
18.0%
1 73048
12.8%
- 60000
10.5%
: 60000
10.5%
30000
 
5.3%
3 26567
 
4.7%
5 23954
 
4.2%
4 23933
 
4.2%
8 14066
 
2.5%
Other values (3) 41906
 
7.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 19000000
100.0%
ValueCountFrequency (%)
(unknown) 570000
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 3798683
20.0%
2 3414072
18.0%
1 2439659
12.8%
: 2000000
10.5%
- 2000000
10.5%
1000000
 
5.3%
3 890067
 
4.7%
5 800311
 
4.2%
4 798703
 
4.2%
7 467556
 
2.5%
Other values (3) 1390949
 
7.3%
ValueCountFrequency (%)
0 114027
20.0%
2 102499
18.0%
1 73048
12.8%
- 60000
10.5%
: 60000
10.5%
30000
 
5.3%
3 26567
 
4.7%
5 23954
 
4.2%
4 23933
 
4.2%
8 14066
 
2.5%
Other values (3) 41906
 
7.4%

product_id
Real number (ℝ)

 Full DatasetSystematic Sample
Distinct99999507
Distinct (%)1.0%31.7%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean4999.5645155014.245233
 Full DatasetSystematic Sample
Minimum11
Maximum99999999
Zeros00
Zeros (%)0.0%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T02:07:54.641638image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Full DatasetSystematic Sample
Minimum11
5-th percentile500512
Q124982507.75
median49995016
Q374987532.25
95-th percentile94999500
Maximum99999999
Range99989998
Interquartile range (IQR)50005024.5

Descriptive statistics

 Full DatasetSystematic Sample
Standard deviation2886.7983912890.88568
Coefficient of variation (CV)0.57740996890.5765345621
Kurtosis-1.200144352-1.207110001
Mean4999.5645155014.245233
Median Absolute Deviation (MAD)25002511
Skewness0.0002346107222-0.004886028745
Sum4999564515150427357
Variance8333604.958357220.013
MonotonicityNot monotonicNot monotonic
2025-06-06T02:07:54.853849image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4898 145
 
< 0.1%
51 143
 
< 0.1%
9593 141
 
< 0.1%
5427 138
 
< 0.1%
3923 137
 
< 0.1%
8365 135
 
< 0.1%
4541 134
 
< 0.1%
2590 134
 
< 0.1%
467 133
 
< 0.1%
3676 133
 
< 0.1%
Other values (9989) 998627
99.9%
ValueCountFrequency (%)
2107 11
 
< 0.1%
9868 11
 
< 0.1%
9170 10
 
< 0.1%
3635 10
 
< 0.1%
9308 10
 
< 0.1%
4355 10
 
< 0.1%
8147 10
 
< 0.1%
4091 10
 
< 0.1%
8255 10
 
< 0.1%
9211 10
 
< 0.1%
Other values (9497) 29898
99.7%
ValueCountFrequency (%)
1 92
< 0.1%
2 107
< 0.1%
3 117
< 0.1%
4 97
< 0.1%
5 92
< 0.1%
ValueCountFrequency (%)
1 2
 
< 0.1%
2 5
< 0.1%
3 2
 
< 0.1%
7 3
< 0.1%
8 4
< 0.1%
ValueCountFrequency (%)
1 2
 
< 0.1%
2 5
< 0.1%
3 2
 
< 0.1%
7 3
< 0.1%
8 4
< 0.1%
ValueCountFrequency (%)
1 92
0.3%
2 107
0.4%
3 117
0.4%
4 97
0.3%
5 92
0.3%

product_category
['Text', 'Text']

 Full DatasetSystematic Sample
Distinct55
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T02:07:55.120871image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

 Full DatasetSystematic Sample
Max length1111
Median length99
Mean length8.1963898.207766667
Min length44

Characters and Unicode

 Full DatasetSystematic Sample
Total characters8196389246233
Distinct characters1818
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Full DatasetSystematic Sample
Unique00 ?
Unique (%)0.0%0.0%

Sample

 Full DatasetSystematic Sample
1st rowElectronicsElectronics
2nd rowGroceriesFurniture
3rd rowToysToys
4th rowToysToys
5th rowClothingGroceries
ValueCountFrequency (%)
toys 200669
20.1%
groceries 200214
20.0%
clothing 199778
20.0%
electronics 199756
20.0%
furniture 199583
20.0%
ValueCountFrequency (%)
electronics 6039
20.1%
furniture 6011
20.0%
groceries 5997
20.0%
clothing 5980
19.9%
toys 5973
19.9%
2025-06-06T02:07:55.482788image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
r 999350
12.2%
o 800417
9.8%
e 799767
9.8%
i 799331
9.8%
s 600639
 
7.3%
c 599726
 
7.3%
n 599117
 
7.3%
t 599117
 
7.3%
l 399534
 
4.9%
u 399166
 
4.9%
Other values (8) 1600225
19.5%
ValueCountFrequency (%)
r 30055
12.2%
e 24044
9.8%
i 24027
9.8%
o 23989
9.7%
c 18075
 
7.3%
t 18030
 
7.3%
n 18030
 
7.3%
s 18009
 
7.3%
u 12022
 
4.9%
l 12019
 
4.9%
Other values (8) 47933
19.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 8196389
100.0%
ValueCountFrequency (%)
(unknown) 246233
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
r 999350
12.2%
o 800417
9.8%
e 799767
9.8%
i 799331
9.8%
s 600639
 
7.3%
c 599726
 
7.3%
n 599117
 
7.3%
t 599117
 
7.3%
l 399534
 
4.9%
u 399166
 
4.9%
Other values (8) 1600225
19.5%
ValueCountFrequency (%)
r 30055
12.2%
e 24044
9.8%
i 24027
9.8%
o 23989
9.7%
c 18075
 
7.3%
t 18030
 
7.3%
n 18030
 
7.3%
s 18009
 
7.3%
u 12022
 
4.9%
l 12019
 
4.9%
Other values (8) 47933
19.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 8196389
100.0%
ValueCountFrequency (%)
(unknown) 246233
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
r 999350
12.2%
o 800417
9.8%
e 799767
9.8%
i 799331
9.8%
s 600639
 
7.3%
c 599726
 
7.3%
n 599117
 
7.3%
t 599117
 
7.3%
l 399534
 
4.9%
u 399166
 
4.9%
Other values (8) 1600225
19.5%
ValueCountFrequency (%)
r 30055
12.2%
e 24044
9.8%
i 24027
9.8%
o 23989
9.7%
c 18075
 
7.3%
t 18030
 
7.3%
n 18030
 
7.3%
s 18009
 
7.3%
u 12022
 
4.9%
l 12019
 
4.9%
Other values (8) 47933
19.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 8196389
100.0%
ValueCountFrequency (%)
(unknown) 246233
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
r 999350
12.2%
o 800417
9.8%
e 799767
9.8%
i 799331
9.8%
s 600639
 
7.3%
c 599726
 
7.3%
n 599117
 
7.3%
t 599117
 
7.3%
l 399534
 
4.9%
u 399166
 
4.9%
Other values (8) 1600225
19.5%
ValueCountFrequency (%)
r 30055
12.2%
e 24044
9.8%
i 24027
9.8%
o 23989
9.7%
c 18075
 
7.3%
t 18030
 
7.3%
n 18030
 
7.3%
s 18009
 
7.3%
u 12022
 
4.9%
l 12019
 
4.9%
Other values (8) 47933
19.5%

quantity
Real number (ℝ)

 Full DatasetSystematic Sample
Distinct99
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean5.0026495.000966667
 Full DatasetSystematic Sample
Minimum11
Maximum99
Zeros00
Zeros (%)0.0%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T02:07:55.580969image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Full DatasetSystematic Sample
Minimum11
5-th percentile11
Q133
median55
Q377
95-th percentile99
Maximum99
Range88
Interquartile range (IQR)44

Descriptive statistics

 Full DatasetSystematic Sample
Standard deviation2.5837512762.586101699
Coefficient of variation (CV)0.5164766260.5171203631
Kurtosis-1.231080652-1.234092138
Mean5.0026495.000966667
Median Absolute Deviation (MAD)22
Skewness-0.00036474606730.003236533329
Sum5002649150029
Variance6.6757706596.687921996
MonotonicityNot monotonicNot monotonic
2025-06-06T02:07:55.680448image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
9 111914
11.2%
3 111422
11.1%
7 111274
11.1%
1 111150
11.1%
4 111104
11.1%
6 111098
11.1%
2 110782
11.1%
8 110747
11.1%
5 110509
11.1%
ValueCountFrequency (%)
7 3386
11.3%
4 3378
11.3%
9 3377
11.3%
2 3352
11.2%
1 3327
11.1%
3 3326
11.1%
5 3321
11.1%
8 3305
11.0%
6 3228
10.8%
ValueCountFrequency (%)
1 111150
11.1%
2 110782
11.1%
3 111422
11.1%
4 111104
11.1%
5 110509
11.1%
ValueCountFrequency (%)
1 3327
11.1%
2 3352
11.2%
3 3326
11.1%
4 3378
11.3%
5 3321
11.1%
ValueCountFrequency (%)
1 3327
0.3%
2 3352
0.3%
3 3326
0.3%
4 3378
0.3%
5 3321
0.3%
ValueCountFrequency (%)
1 111150
370.5%
2 110782
369.3%
3 111422
371.4%
4 111104
370.3%
5 110509
368.4%

unit_price
Real number (ℝ)

 Full DatasetSystematic Sample
Distinct9989625968
Distinct (%)10.0%86.6%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean500.2613169499.58365
 Full DatasetSystematic Sample
Minimum11.06
Maximum1000999.98
Zeros00
Zeros (%)0.0%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T02:07:55.874134image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Full DatasetSystematic Sample
Minimum11.06
5-th percentile50.7249.436
Q1250.31252.1225
median500.41499.915
Q3750.16748.18
95-th percentile949.91948.981
Maximum1000999.98
Range999998.92
Interquartile range (IQR)499.85496.0575

Descriptive statistics

 Full DatasetSystematic Sample
Standard deviation288.4628596287.9481681
Coefficient of variation (CV)0.57662435590.5763762846
Kurtosis-1.20144233-1.194704901
Mean500.2613169499.58365
Median Absolute Deviation (MAD)249.93248.13
Skewness-1.097330655 × 10-5-0.002188554165
Sum500261316.914987509.5
Variance83210.8213982914.14749
MonotonicityNot monotonicNot monotonic
2025-06-06T02:07:56.395619image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
226.51 28
 
< 0.1%
450.02 26
 
< 0.1%
591.8 25
 
< 0.1%
921.47 25
 
< 0.1%
354.83 25
 
< 0.1%
49.69 25
 
< 0.1%
111.41 24
 
< 0.1%
954.1 24
 
< 0.1%
619.19 24
 
< 0.1%
845.21 24
 
< 0.1%
Other values (99886) 999750
> 99.9%
ValueCountFrequency (%)
40.62 4
 
< 0.1%
602.8 4
 
< 0.1%
350.29 4
 
< 0.1%
352.5 4
 
< 0.1%
38.58 4
 
< 0.1%
573.88 4
 
< 0.1%
965.77 4
 
< 0.1%
957.31 4
 
< 0.1%
13.93 4
 
< 0.1%
999.13 4
 
< 0.1%
Other values (25958) 29960
99.9%
ValueCountFrequency (%)
1 7
< 0.1%
1.01 9
< 0.1%
1.02 11
< 0.1%
1.03 8
< 0.1%
1.04 17
< 0.1%
ValueCountFrequency (%)
1.06 2
< 0.1%
1.09 1
< 0.1%
1.1 1
< 0.1%
1.12 1
< 0.1%
1.2 1
< 0.1%
ValueCountFrequency (%)
1.06 2
< 0.1%
1.09 1
< 0.1%
1.1 1
< 0.1%
1.12 1
< 0.1%
1.2 1
< 0.1%
ValueCountFrequency (%)
1 7
< 0.1%
1.01 9
< 0.1%
1.02 11
< 0.1%
1.03 8
< 0.1%
1.04 17
0.1%

discount_applied
Real number (ℝ)

 Full DatasetSystematic Sample
Distinct5151
Distinct (%)< 0.1%0.2%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean0.249910490.2486653333
 Full DatasetSystematic Sample
Minimum00
Maximum0.50.5
Zeros9967317
Zeros (%)1.0%1.1%
Negative00
Negative (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T02:07:56.603587image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Full DatasetSystematic Sample
Minimum00
5-th percentile0.030.02
Q10.130.12
median0.250.25
Q30.370.37
95-th percentile0.470.47
Maximum0.50.5
Range0.50.5
Interquartile range (IQR)0.240.25

Descriptive statistics

 Full DatasetSystematic Sample
Standard deviation0.14432790830.1442589767
Coefficient of variation (CV)0.57751840790.5801330437
Kurtosis-1.19713108-1.193243353
Mean0.249910490.2486653333
Median Absolute Deviation (MAD)0.120.13
Skewness0.00026409763360.01196552323
Sum249910.497459.96
Variance0.020830545120.02081065235
MonotonicityNot monotonicNot monotonic
2025-06-06T02:07:56.812666image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.19 20302
 
2.0%
0.06 20213
 
2.0%
0.34 20211
 
2.0%
0.03 20207
 
2.0%
0.05 20207
 
2.0%
0.21 20199
 
2.0%
0.29 20155
 
2.0%
0.07 20153
 
2.0%
0.43 20145
 
2.0%
0.18 20111
 
2.0%
Other values (41) 798097
79.8%
ValueCountFrequency (%)
0.07 659
 
2.2%
0.39 642
 
2.1%
0.19 636
 
2.1%
0.21 636
 
2.1%
0.12 627
 
2.1%
0.43 627
 
2.1%
0.25 625
 
2.1%
0.17 624
 
2.1%
0.01 623
 
2.1%
0.18 622
 
2.1%
Other values (41) 23679
78.9%
ValueCountFrequency (%)
0 9967
1.0%
0.01 20018
2.0%
0.02 19788
2.0%
0.03 20207
2.0%
0.04 19947
2.0%
ValueCountFrequency (%)
0 317
1.1%
0.01 623
2.1%
0.02 594
2.0%
0.03 585
1.9%
0.04 604
2.0%
ValueCountFrequency (%)
0 317
< 0.1%
0.01 623
0.1%
0.02 594
0.1%
0.03 585
0.1%
0.04 604
0.1%
ValueCountFrequency (%)
0 9967
33.2%
0.01 20018
66.7%
0.02 19788
66.0%
0.03 20207
67.4%
0.04 19947
66.5%

payment_method
['Text', 'Text']

 Full DatasetSystematic Sample
Distinct44
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T02:07:57.072014image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

 Full DatasetSystematic Sample
Max length1414
Median length1111
Mean length9.7519359.763566667
Min length44

Characters and Unicode

 Full DatasetSystematic Sample
Total characters9751935292907
Distinct characters1919
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Full DatasetSystematic Sample
Unique00 ?
Unique (%)0.0%0.0%

Sample

 Full DatasetSystematic Sample
1st rowCredit CardCredit Card
2nd rowCredit CardMobile Payment
3rd rowDebit CardCash
4th rowCredit CardCash
5th rowMobile PaymentCash
ValueCountFrequency (%)
card 500200
28.6%
credit 250435
14.3%
mobile 250030
14.3%
payment 250030
14.3%
cash 249770
14.3%
debit 249765
14.3%
ValueCountFrequency (%)
card 15048
28.6%
debit 7579
14.4%
mobile 7515
14.3%
payment 7515
14.3%
credit 7469
14.2%
cash 7437
14.1%
2025-06-06T02:07:57.389518image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
C 1000405
10.3%
e 1000260
10.3%
a 1000000
10.3%
r 750635
 
7.7%
d 750635
 
7.7%
t 750230
 
7.7%
i 750230
 
7.7%
750230
 
7.7%
b 499795
 
5.1%
M 250030
 
2.6%
Other values (9) 2249485
23.1%
ValueCountFrequency (%)
e 30078
10.3%
a 30000
10.2%
C 29954
10.2%
22563
 
7.7%
i 22563
 
7.7%
t 22563
 
7.7%
r 22517
 
7.7%
d 22517
 
7.7%
b 15094
 
5.2%
D 7579
 
2.6%
Other values (9) 67479
23.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 9751935
100.0%
ValueCountFrequency (%)
(unknown) 292907
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
C 1000405
10.3%
e 1000260
10.3%
a 1000000
10.3%
r 750635
 
7.7%
d 750635
 
7.7%
t 750230
 
7.7%
i 750230
 
7.7%
750230
 
7.7%
b 499795
 
5.1%
M 250030
 
2.6%
Other values (9) 2249485
23.1%
ValueCountFrequency (%)
e 30078
10.3%
a 30000
10.2%
C 29954
10.2%
22563
 
7.7%
i 22563
 
7.7%
t 22563
 
7.7%
r 22517
 
7.7%
d 22517
 
7.7%
b 15094
 
5.2%
D 7579
 
2.6%
Other values (9) 67479
23.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 9751935
100.0%
ValueCountFrequency (%)
(unknown) 292907
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
C 1000405
10.3%
e 1000260
10.3%
a 1000000
10.3%
r 750635
 
7.7%
d 750635
 
7.7%
t 750230
 
7.7%
i 750230
 
7.7%
750230
 
7.7%
b 499795
 
5.1%
M 250030
 
2.6%
Other values (9) 2249485
23.1%
ValueCountFrequency (%)
e 30078
10.3%
a 30000
10.2%
C 29954
10.2%
22563
 
7.7%
i 22563
 
7.7%
t 22563
 
7.7%
r 22517
 
7.7%
d 22517
 
7.7%
b 15094
 
5.2%
D 7579
 
2.6%
Other values (9) 67479
23.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 9751935
100.0%
ValueCountFrequency (%)
(unknown) 292907
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
C 1000405
10.3%
e 1000260
10.3%
a 1000000
10.3%
r 750635
 
7.7%
d 750635
 
7.7%
t 750230
 
7.7%
i 750230
 
7.7%
750230
 
7.7%
b 499795
 
5.1%
M 250030
 
2.6%
Other values (9) 2249485
23.1%
ValueCountFrequency (%)
e 30078
10.3%
a 30000
10.2%
C 29954
10.2%
22563
 
7.7%
i 22563
 
7.7%
t 22563
 
7.7%
r 22517
 
7.7%
d 22517
 
7.7%
b 15094
 
5.2%
D 7579
 
2.6%
Other values (9) 67479
23.0%

store_location
['Text', 'Text']

 Full DatasetSystematic Sample
Distinct44
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T02:07:57.574055image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

 Full DatasetSystematic Sample
Max length1010
Median length1010
Mean length1010
Min length1010

Characters and Unicode

 Full DatasetSystematic Sample
Total characters10000000300000
Distinct characters1212
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Full DatasetSystematic Sample
Unique00 ?
Unique (%)0.0%0.0%

Sample

 Full DatasetSystematic Sample
1st rowLocation ALocation A
2nd rowLocation CLocation A
3rd rowLocation ALocation C
4th rowLocation ALocation A
5th rowLocation CLocation B
ValueCountFrequency (%)
location 1000000
50.0%
c 250336
 
12.5%
b 250280
 
12.5%
a 250150
 
12.5%
d 249234
 
12.5%
ValueCountFrequency (%)
location 30000
50.0%
a 7612
 
12.7%
c 7515
 
12.5%
b 7462
 
12.4%
d 7411
 
12.4%
2025-06-06T02:07:57.858481image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 2000000
20.0%
L 1000000
10.0%
c 1000000
10.0%
a 1000000
10.0%
t 1000000
10.0%
i 1000000
10.0%
n 1000000
10.0%
1000000
10.0%
C 250336
 
2.5%
B 250280
 
2.5%
Other values (2) 499384
 
5.0%
ValueCountFrequency (%)
o 60000
20.0%
L 30000
10.0%
c 30000
10.0%
a 30000
10.0%
t 30000
10.0%
i 30000
10.0%
n 30000
10.0%
30000
10.0%
A 7612
 
2.5%
C 7515
 
2.5%
Other values (2) 14873
 
5.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 10000000
100.0%
ValueCountFrequency (%)
(unknown) 300000
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
o 2000000
20.0%
L 1000000
10.0%
c 1000000
10.0%
a 1000000
10.0%
t 1000000
10.0%
i 1000000
10.0%
n 1000000
10.0%
1000000
10.0%
C 250336
 
2.5%
B 250280
 
2.5%
Other values (2) 499384
 
5.0%
ValueCountFrequency (%)
o 60000
20.0%
L 30000
10.0%
c 30000
10.0%
a 30000
10.0%
t 30000
10.0%
i 30000
10.0%
n 30000
10.0%
30000
10.0%
A 7612
 
2.5%
C 7515
 
2.5%
Other values (2) 14873
 
5.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 10000000
100.0%
ValueCountFrequency (%)
(unknown) 300000
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
o 2000000
20.0%
L 1000000
10.0%
c 1000000
10.0%
a 1000000
10.0%
t 1000000
10.0%
i 1000000
10.0%
n 1000000
10.0%
1000000
10.0%
C 250336
 
2.5%
B 250280
 
2.5%
Other values (2) 499384
 
5.0%
ValueCountFrequency (%)
o 60000
20.0%
L 30000
10.0%
c 30000
10.0%
a 30000
10.0%
t 30000
10.0%
i 30000
10.0%
n 30000
10.0%
30000
10.0%
A 7612
 
2.5%
C 7515
 
2.5%
Other values (2) 14873
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 10000000
100.0%
ValueCountFrequency (%)
(unknown) 300000
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
o 2000000
20.0%
L 1000000
10.0%
c 1000000
10.0%
a 1000000
10.0%
t 1000000
10.0%
i 1000000
10.0%
n 1000000
10.0%
1000000
10.0%
C 250336
 
2.5%
B 250280
 
2.5%
Other values (2) 499384
 
5.0%
ValueCountFrequency (%)
o 60000
20.0%
L 30000
10.0%
c 30000
10.0%
a 30000
10.0%
t 30000
10.0%
i 30000
10.0%
n 30000
10.0%
30000
10.0%
A 7612
 
2.5%
C 7515
 
2.5%
Other values (2) 14873
 
5.0%

transaction_hour
Real number (ℝ)

 Full DatasetSystematic Sample
Distinct2424
Distinct (%)< 0.1%0.1%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean11.50519311.48146667
 Full DatasetSystematic Sample
Minimum00
Maximum2323
Zeros417561312
Zeros (%)4.2%4.4%
Negative00
Negative (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T02:07:57.989787image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Full DatasetSystematic Sample
Minimum00
5-th percentile11
Q155
median1212
Q31817
95-th percentile2222
Maximum2323
Range2323
Interquartile range (IQR)1312

Descriptive statistics

 Full DatasetSystematic Sample
Standard deviation6.9244597616.931358066
Coefficient of variation (CV)0.60185515890.6036997073
Kurtosis-1.205305317-1.205421909
Mean11.50519311.48146667
Median Absolute Deviation (MAD)66
Skewness-0.001531297707-0.004865786085
Sum11505193344444
Variance47.9481429848.04372464
MonotonicityNot monotonicNot monotonic
2025-06-06T02:07:58.128141image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
5 42166
 
4.2%
14 42161
 
4.2%
18 41872
 
4.2%
20 41812
 
4.2%
3 41780
 
4.2%
21 41778
 
4.2%
4 41756
 
4.2%
0 41756
 
4.2%
23 41750
 
4.2%
19 41707
 
4.2%
Other values (14) 581462
58.1%
ValueCountFrequency (%)
0 1312
 
4.4%
16 1300
 
4.3%
6 1285
 
4.3%
17 1284
 
4.3%
13 1281
 
4.3%
3 1279
 
4.3%
1 1267
 
4.2%
22 1259
 
4.2%
12 1259
 
4.2%
20 1253
 
4.2%
Other values (14) 17221
57.4%
ValueCountFrequency (%)
0 41756
4.2%
1 41637
4.2%
2 41388
4.1%
3 41780
4.2%
4 41756
4.2%
ValueCountFrequency (%)
0 1312
4.4%
1 1267
4.2%
2 1213
4.0%
3 1279
4.3%
4 1213
4.0%
ValueCountFrequency (%)
0 1312
0.1%
1 1267
0.1%
2 1213
0.1%
3 1279
0.1%
4 1213
0.1%
ValueCountFrequency (%)
0 41756
139.2%
1 41637
138.8%
2 41388
138.0%
3 41780
139.3%
4 41756
139.2%

day_of_week
['Text', 'Text']

 Full DatasetSystematic Sample
Distinct77
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T02:07:58.407313image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

 Full DatasetSystematic Sample
Max length99
Median length88
Mean length7.1410757.1391
Min length66

Characters and Unicode

 Full DatasetSystematic Sample
Total characters7141075214173
Distinct characters1717
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Full DatasetSystematic Sample
Unique00 ?
Unique (%)0.0%0.0%

Sample

 Full DatasetSystematic Sample
1st rowWednesdayWednesday
2nd rowFridayFriday
3rd rowSaturdayFriday
4th rowFridayFriday
5th rowMondayWednesday
ValueCountFrequency (%)
tuesday 143452
14.3%
friday 143067
14.3%
thursday 142930
14.3%
sunday 142875
14.3%
monday 142855
14.3%
saturday 142700
14.3%
wednesday 142121
14.2%
ValueCountFrequency (%)
sunday 4392
14.6%
saturday 4301
14.3%
thursday 4271
14.2%
friday 4269
14.2%
wednesday 4258
14.2%
tuesday 4255
14.2%
monday 4254
14.2%
2025-06-06T02:07:58.772328image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 1142700
16.0%
d 1142121
16.0%
y 1000000
14.0%
u 571957
8.0%
r 428697
 
6.0%
s 428503
 
6.0%
n 427851
 
6.0%
e 427694
 
6.0%
T 286382
 
4.0%
S 285575
 
4.0%
Other values (7) 999595
14.0%
ValueCountFrequency (%)
a 34301
16.0%
d 34258
16.0%
y 30000
14.0%
u 17219
8.0%
n 12904
 
6.0%
r 12841
 
6.0%
s 12784
 
6.0%
e 12771
 
6.0%
S 8693
 
4.1%
T 8526
 
4.0%
Other values (7) 29876
13.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 7141075
100.0%
ValueCountFrequency (%)
(unknown) 214173
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 1142700
16.0%
d 1142121
16.0%
y 1000000
14.0%
u 571957
8.0%
r 428697
 
6.0%
s 428503
 
6.0%
n 427851
 
6.0%
e 427694
 
6.0%
T 286382
 
4.0%
S 285575
 
4.0%
Other values (7) 999595
14.0%
ValueCountFrequency (%)
a 34301
16.0%
d 34258
16.0%
y 30000
14.0%
u 17219
8.0%
n 12904
 
6.0%
r 12841
 
6.0%
s 12784
 
6.0%
e 12771
 
6.0%
S 8693
 
4.1%
T 8526
 
4.0%
Other values (7) 29876
13.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 7141075
100.0%
ValueCountFrequency (%)
(unknown) 214173
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 1142700
16.0%
d 1142121
16.0%
y 1000000
14.0%
u 571957
8.0%
r 428697
 
6.0%
s 428503
 
6.0%
n 427851
 
6.0%
e 427694
 
6.0%
T 286382
 
4.0%
S 285575
 
4.0%
Other values (7) 999595
14.0%
ValueCountFrequency (%)
a 34301
16.0%
d 34258
16.0%
y 30000
14.0%
u 17219
8.0%
n 12904
 
6.0%
r 12841
 
6.0%
s 12784
 
6.0%
e 12771
 
6.0%
S 8693
 
4.1%
T 8526
 
4.0%
Other values (7) 29876
13.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 7141075
100.0%
ValueCountFrequency (%)
(unknown) 214173
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 1142700
16.0%
d 1142121
16.0%
y 1000000
14.0%
u 571957
8.0%
r 428697
 
6.0%
s 428503
 
6.0%
n 427851
 
6.0%
e 427694
 
6.0%
T 286382
 
4.0%
S 285575
 
4.0%
Other values (7) 999595
14.0%
ValueCountFrequency (%)
a 34301
16.0%
d 34258
16.0%
y 30000
14.0%
u 17219
8.0%
n 12904
 
6.0%
r 12841
 
6.0%
s 12784
 
6.0%
e 12771
 
6.0%
S 8693
 
4.1%
T 8526
 
4.0%
Other values (7) 29876
13.9%

week_of_year
Real number (ℝ)

 Full DatasetSystematic Sample
Distinct5252
Distinct (%)< 0.1%0.2%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean26.50369126.4998
 Full DatasetSystematic Sample
Minimum11
Maximum5252
Zeros00
Zeros (%)0.0%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T02:07:58.954774image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Full DatasetSystematic Sample
Minimum11
5-th percentile33
Q11414
median2727
Q33939.25
95-th percentile5050
Maximum5252
Range5151
Interquartile range (IQR)2525.25

Descriptive statistics

 Full DatasetSystematic Sample
Standard deviation15.0051651615.02027475
Coefficient of variation (CV)0.5661537920.5668070986
Kurtosis-1.199199248-1.198848872
Mean26.50369126.4998
Median Absolute Deviation (MAD)1313
Skewness-0.0005909978351-0.005785736997
Sum26503691794994
Variance225.1549815225.6086536
MonotonicityNot monotonicNot monotonic
2025-06-06T02:07:59.152761image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
27 19588
 
2.0%
19 19507
 
2.0%
51 19447
 
1.9%
26 19425
 
1.9%
1 19399
 
1.9%
25 19386
 
1.9%
21 19371
 
1.9%
44 19356
 
1.9%
16 19348
 
1.9%
9 19340
 
1.9%
Other values (42) 805833
80.6%
ValueCountFrequency (%)
19 624
 
2.1%
2 622
 
2.1%
46 611
 
2.0%
48 611
 
2.0%
44 605
 
2.0%
33 603
 
2.0%
8 603
 
2.0%
28 601
 
2.0%
24 601
 
2.0%
10 598
 
2.0%
Other values (42) 23921
79.7%
ValueCountFrequency (%)
1 19399
1.9%
2 19179
1.9%
3 19150
1.9%
4 19137
1.9%
5 19328
1.9%
ValueCountFrequency (%)
1 584
1.9%
2 622
2.1%
3 594
2.0%
4 581
1.9%
5 561
1.9%
ValueCountFrequency (%)
1 584
0.1%
2 622
0.1%
3 594
0.1%
4 581
0.1%
5 561
0.1%
ValueCountFrequency (%)
1 19399
64.7%
2 19179
63.9%
3 19150
63.8%
4 19137
63.8%
5 19328
64.4%

month_of_year
Real number (ℝ)

 Full DatasetSystematic Sample
Distinct1212
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean6.4974676.524033333
 Full DatasetSystematic Sample
Minimum11
Maximum1212
Zeros00
Zeros (%)0.0%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T02:07:59.351683image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Full DatasetSystematic Sample
Minimum11
5-th percentile11
Q134
median77
Q31010
95-th percentile1212
Maximum1212
Range1111
Interquartile range (IQR)76

Descriptive statistics

 Full DatasetSystematic Sample
Standard deviation3.4552119363.457719035
Coefficient of variation (CV)0.5317782970.5299971442
Kurtosis-1.21903855-1.225186228
Mean6.4974676.524033333
Median Absolute Deviation (MAD)33
Skewness0.0003820436436-0.01077981305
Sum6497467195721
Variance11.9384895211.95582093
MonotonicityNot monotonicNot monotonic
2025-06-06T02:07:59.526817image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
2 83951
8.4%
11 83645
8.4%
1 83624
8.4%
7 83475
8.3%
12 83353
8.3%
9 83328
8.3%
3 83244
8.3%
5 83135
8.3%
10 83113
8.3%
8 83093
8.3%
Other values (2) 166039
16.6%
ValueCountFrequency (%)
10 2589
8.6%
9 2562
8.5%
2 2553
8.5%
12 2535
8.5%
8 2496
8.3%
6 2492
8.3%
3 2478
8.3%
11 2475
8.2%
4 2470
8.2%
5 2466
8.2%
Other values (2) 4884
16.3%
ValueCountFrequency (%)
1 83624
8.4%
2 83951
8.4%
3 83244
8.3%
4 83091
8.3%
5 83135
8.3%
ValueCountFrequency (%)
1 2455
8.2%
2 2553
8.5%
3 2478
8.3%
4 2470
8.2%
5 2466
8.2%
ValueCountFrequency (%)
1 2455
0.2%
2 2553
0.3%
3 2478
0.2%
4 2470
0.2%
5 2466
0.2%
ValueCountFrequency (%)
1 83624
278.7%
2 83951
279.8%
3 83244
277.5%
4 83091
277.0%
5 83135
277.1%

avg_purchase_value
Real number (ℝ)

 Full DatasetSystematic Sample
Distinct4900122551
Distinct (%)4.9%75.2%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean254.8864443256.1898827
 Full DatasetSystematic Sample
Minimum1010
Maximum500499.96
Zeros00
Zeros (%)0.0%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T02:07:59.772400image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Full DatasetSystematic Sample
Minimum1010
5-th percentile34.434.4295
Q1132.22133.445
median254.93256.425
Q3377.35377.93
95-th percentile475.56476.8705
Maximum500499.96
Range490489.96
Interquartile range (IQR)245.13244.485

Descriptive statistics

 Full DatasetSystematic Sample
Standard deviation141.4949233141.9802413
Coefficient of variation (CV)0.55512926040.5541992518
Kurtosis-1.200170422-1.197255262
Mean254.8864443256.1898827
Median Absolute Deviation (MAD)122.57122.275
Skewness0.0003762833586-0.008478684966
Sum254886444.37685696.48
Variance20020.8133320158.38892
MonotonicityNot monotonicNot monotonic
2025-06-06T02:08:00.106340image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
76.54 41
 
< 0.1%
482.75 41
 
< 0.1%
372.04 40
 
< 0.1%
397.45 39
 
< 0.1%
246.87 39
 
< 0.1%
60.53 38
 
< 0.1%
278.34 38
 
< 0.1%
315.26 38
 
< 0.1%
165.81 38
 
< 0.1%
492.47 38
 
< 0.1%
Other values (48991) 999610
> 99.9%
ValueCountFrequency (%)
236.57 6
 
< 0.1%
65.97 6
 
< 0.1%
291.76 6
 
< 0.1%
372.13 6
 
< 0.1%
335.61 5
 
< 0.1%
170.11 5
 
< 0.1%
58.11 5
 
< 0.1%
134.34 5
 
< 0.1%
230.67 5
 
< 0.1%
392.45 5
 
< 0.1%
Other values (22541) 29946
99.8%
ValueCountFrequency (%)
10 8
 
< 0.1%
10.01 23
< 0.1%
10.02 29
< 0.1%
10.03 17
< 0.1%
10.04 21
< 0.1%
ValueCountFrequency (%)
10 1
< 0.1%
10.03 1
< 0.1%
10.04 1
< 0.1%
10.05 1
< 0.1%
10.07 2
< 0.1%
ValueCountFrequency (%)
10 1
< 0.1%
10.03 1
< 0.1%
10.04 1
< 0.1%
10.05 1
< 0.1%
10.07 2
< 0.1%
ValueCountFrequency (%)
10 8
 
< 0.1%
10.01 23
0.1%
10.02 29
0.1%
10.03 17
0.1%
10.04 21
0.1%

purchase_frequency
['Text', 'Text']

 Full DatasetSystematic Sample
Distinct44
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T02:08:00.505105image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

 Full DatasetSystematic Sample
Max length77
Median length66
Mean length6.0003995.993833333
Min length55

Characters and Unicode

 Full DatasetSystematic Sample
Total characters6000399179815
Distinct characters1515
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Full DatasetSystematic Sample
Unique00 ?
Unique (%)0.0%0.0%

Sample

 Full DatasetSystematic Sample
1st rowWeeklyWeekly
2nd rowDailyYearly
3rd rowWeeklyYearly
4th rowWeeklyWeekly
5th rowYearlyMonthly
ValueCountFrequency (%)
yearly 250767
25.1%
monthly 249932
25.0%
weekly 249768
25.0%
daily 249533
25.0%
ValueCountFrequency (%)
daily 7569
25.2%
yearly 7529
25.1%
weekly 7518
25.1%
monthly 7384
24.6%
2025-06-06T02:08:01.009348image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
l 1000000
16.7%
y 1000000
16.7%
e 750303
12.5%
a 500300
8.3%
Y 250767
 
4.2%
r 250767
 
4.2%
M 249932
 
4.2%
o 249932
 
4.2%
n 249932
 
4.2%
t 249932
 
4.2%
Other values (5) 1248534
20.8%
ValueCountFrequency (%)
l 30000
16.7%
y 30000
16.7%
e 22565
12.5%
a 15098
8.4%
D 7569
 
4.2%
i 7569
 
4.2%
Y 7529
 
4.2%
r 7529
 
4.2%
W 7518
 
4.2%
k 7518
 
4.2%
Other values (5) 36920
20.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 6000399
100.0%
ValueCountFrequency (%)
(unknown) 179815
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
l 1000000
16.7%
y 1000000
16.7%
e 750303
12.5%
a 500300
8.3%
Y 250767
 
4.2%
r 250767
 
4.2%
M 249932
 
4.2%
o 249932
 
4.2%
n 249932
 
4.2%
t 249932
 
4.2%
Other values (5) 1248534
20.8%
ValueCountFrequency (%)
l 30000
16.7%
y 30000
16.7%
e 22565
12.5%
a 15098
8.4%
D 7569
 
4.2%
i 7569
 
4.2%
Y 7529
 
4.2%
r 7529
 
4.2%
W 7518
 
4.2%
k 7518
 
4.2%
Other values (5) 36920
20.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 6000399
100.0%
ValueCountFrequency (%)
(unknown) 179815
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
l 1000000
16.7%
y 1000000
16.7%
e 750303
12.5%
a 500300
8.3%
Y 250767
 
4.2%
r 250767
 
4.2%
M 249932
 
4.2%
o 249932
 
4.2%
n 249932
 
4.2%
t 249932
 
4.2%
Other values (5) 1248534
20.8%
ValueCountFrequency (%)
l 30000
16.7%
y 30000
16.7%
e 22565
12.5%
a 15098
8.4%
D 7569
 
4.2%
i 7569
 
4.2%
Y 7529
 
4.2%
r 7529
 
4.2%
W 7518
 
4.2%
k 7518
 
4.2%
Other values (5) 36920
20.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 6000399
100.0%
ValueCountFrequency (%)
(unknown) 179815
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
l 1000000
16.7%
y 1000000
16.7%
e 750303
12.5%
a 500300
8.3%
Y 250767
 
4.2%
r 250767
 
4.2%
M 249932
 
4.2%
o 249932
 
4.2%
n 249932
 
4.2%
t 249932
 
4.2%
Other values (5) 1248534
20.8%
ValueCountFrequency (%)
l 30000
16.7%
y 30000
16.7%
e 22565
12.5%
a 15098
8.4%
D 7569
 
4.2%
i 7569
 
4.2%
Y 7529
 
4.2%
r 7529
 
4.2%
W 7518
 
4.2%
k 7518
 
4.2%
Other values (5) 36920
20.5%

last_purchase_date
['Text', 'Text']

 Full DatasetSystematic Sample
Distinct98424229978
Distinct (%)98.4%99.9%
Missing00
Missing (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T02:08:02.050635image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

 Full DatasetSystematic Sample
Max length1919
Median length1919
Mean length1919
Min length1919

Characters and Unicode

 Full DatasetSystematic Sample
Total characters19000000570000
Distinct characters1313
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Full DatasetSystematic Sample
Unique96865629956 ?
Unique (%)96.9%99.9%

Sample

 Full DatasetSystematic Sample
1st row2021-09-11 04:22:382021-09-11 04:22:38
2nd row2021-05-16 12:01:162021-07-06 13:17:09
3rd row2021-02-07 16:47:482021-12-20 08:00:19
4th row2021-12-30 23:48:262021-12-02 07:30:26
5th row2021-11-02 11:48:252021-10-27 01:27:24
ValueCountFrequency (%)
2021-01-02 2870
 
0.1%
2021-05-14 2866
 
0.1%
2021-12-25 2860
 
0.1%
2021-01-17 2860
 
0.1%
2021-10-17 2856
 
0.1%
2021-01-26 2856
 
0.1%
2021-08-16 2854
 
0.1%
2021-05-05 2852
 
0.1%
2021-10-16 2850
 
0.1%
2021-09-17 2849
 
0.1%
Other values (86754) 1971427
98.6%
ValueCountFrequency (%)
2021-11-25 110
 
0.2%
2021-05-04 107
 
0.2%
2021-06-17 104
 
0.2%
2021-03-13 104
 
0.2%
2021-03-12 104
 
0.2%
2021-08-02 104
 
0.2%
2021-08-22 103
 
0.2%
2021-03-01 103
 
0.2%
2021-04-22 102
 
0.2%
2021-09-18 101
 
0.2%
Other values (25779) 58958
98.3%
2025-06-06T02:08:03.072347image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 3411647
18.0%
0 3298747
17.4%
1 2941758
15.5%
- 2000000
10.5%
: 2000000
10.5%
1000000
 
5.3%
3 891719
 
4.7%
5 800287
 
4.2%
4 796296
 
4.2%
7 466826
 
2.5%
Other values (3) 1392720
7.3%
ValueCountFrequency (%)
2 102083
17.9%
0 99290
17.4%
1 88049
15.4%
- 60000
10.5%
: 60000
10.5%
30000
 
5.3%
3 26911
 
4.7%
5 24014
 
4.2%
4 23745
 
4.2%
6 14062
 
2.5%
Other values (3) 41846
7.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 19000000
100.0%
ValueCountFrequency (%)
(unknown) 570000
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
2 3411647
18.0%
0 3298747
17.4%
1 2941758
15.5%
- 2000000
10.5%
: 2000000
10.5%
1000000
 
5.3%
3 891719
 
4.7%
5 800287
 
4.2%
4 796296
 
4.2%
7 466826
 
2.5%
Other values (3) 1392720
7.3%
ValueCountFrequency (%)
2 102083
17.9%
0 99290
17.4%
1 88049
15.4%
- 60000
10.5%
: 60000
10.5%
30000
 
5.3%
3 26911
 
4.7%
5 24014
 
4.2%
4 23745
 
4.2%
6 14062
 
2.5%
Other values (3) 41846
7.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 19000000
100.0%
ValueCountFrequency (%)
(unknown) 570000
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
2 3411647
18.0%
0 3298747
17.4%
1 2941758
15.5%
- 2000000
10.5%
: 2000000
10.5%
1000000
 
5.3%
3 891719
 
4.7%
5 800287
 
4.2%
4 796296
 
4.2%
7 466826
 
2.5%
Other values (3) 1392720
7.3%
ValueCountFrequency (%)
2 102083
17.9%
0 99290
17.4%
1 88049
15.4%
- 60000
10.5%
: 60000
10.5%
30000
 
5.3%
3 26911
 
4.7%
5 24014
 
4.2%
4 23745
 
4.2%
6 14062
 
2.5%
Other values (3) 41846
7.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 19000000
100.0%
ValueCountFrequency (%)
(unknown) 570000
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
2 3411647
18.0%
0 3298747
17.4%
1 2941758
15.5%
- 2000000
10.5%
: 2000000
10.5%
1000000
 
5.3%
3 891719
 
4.7%
5 800287
 
4.2%
4 796296
 
4.2%
7 466826
 
2.5%
Other values (3) 1392720
7.3%
ValueCountFrequency (%)
2 102083
17.9%
0 99290
17.4%
1 88049
15.4%
- 60000
10.5%
: 60000
10.5%
30000
 
5.3%
3 26911
 
4.7%
5 24014
 
4.2%
4 23745
 
4.2%
6 14062
 
2.5%
Other values (3) 41846
7.3%

avg_discount_used
Real number (ℝ)

 Full DatasetSystematic Sample
Distinct5151
Distinct (%)< 0.1%0.2%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean0.250010090.2499986667
 Full DatasetSystematic Sample
Minimum00
Maximum0.50.5
Zeros10010294
Zeros (%)1.0%1.0%
Negative00
Negative (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T02:08:03.268620image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Full DatasetSystematic Sample
Minimum00
5-th percentile0.030.02
Q10.130.13
median0.250.25
Q30.380.38
95-th percentile0.470.48
Maximum0.50.5
Range0.50.5
Interquartile range (IQR)0.250.25

Descriptive statistics

 Full DatasetSystematic Sample
Standard deviation0.14438256280.1446056604
Coefficient of variation (CV)0.57750694310.5784257266
Kurtosis-1.19810725-1.198616805
Mean0.250010090.2499986667
Median Absolute Deviation (MAD)0.120.13
Skewness0.0002818589406-0.001666434333
Sum250010.097499.96
Variance0.020846324440.02091079702
MonotonicityNot monotonicNot monotonic
2025-06-06T02:08:03.480865image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.39 20194
 
2.0%
0.15 20188
 
2.0%
0.08 20140
 
2.0%
0.21 20138
 
2.0%
0.34 20131
 
2.0%
0.47 20125
 
2.0%
0.05 20124
 
2.0%
0.16 20123
 
2.0%
0.46 20109
 
2.0%
0.32 20093
 
2.0%
Other values (41) 798635
79.9%
ValueCountFrequency (%)
0.26 639
 
2.1%
0.13 637
 
2.1%
0.08 636
 
2.1%
0.46 636
 
2.1%
0.28 632
 
2.1%
0.31 628
 
2.1%
0.14 626
 
2.1%
0.03 625
 
2.1%
0.05 621
 
2.1%
0.39 620
 
2.1%
Other values (41) 23700
79.0%
ValueCountFrequency (%)
0 10010
1.0%
0.01 19893
2.0%
0.02 19951
2.0%
0.03 19949
2.0%
0.04 20004
2.0%
ValueCountFrequency (%)
0 294
1.0%
0.01 617
2.1%
0.02 607
2.0%
0.03 625
2.1%
0.04 599
2.0%
ValueCountFrequency (%)
0 294
< 0.1%
0.01 617
0.1%
0.02 607
0.1%
0.03 625
0.1%
0.04 599
0.1%
ValueCountFrequency (%)
0 10010
33.4%
0.01 19893
66.3%
0.02 19951
66.5%
0.03 19949
66.5%
0.04 20004
66.7%

preferred_store
['Text', 'Text']

 Full DatasetSystematic Sample
Distinct44
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T02:08:03.703519image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

 Full DatasetSystematic Sample
Max length1010
Median length1010
Mean length1010
Min length1010

Characters and Unicode

 Full DatasetSystematic Sample
Total characters10000000300000
Distinct characters1212
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Full DatasetSystematic Sample
Unique00 ?
Unique (%)0.0%0.0%

Sample

 Full DatasetSystematic Sample
1st rowLocation ALocation A
2nd rowLocation CLocation D
3rd rowLocation BLocation A
4th rowLocation BLocation B
5th rowLocation BLocation C
ValueCountFrequency (%)
location 1000000
50.0%
b 250262
 
12.5%
d 250007
 
12.5%
a 249949
 
12.5%
c 249782
 
12.5%
ValueCountFrequency (%)
location 30000
50.0%
a 7580
 
12.6%
b 7569
 
12.6%
c 7467
 
12.4%
d 7384
 
12.3%
2025-06-06T02:08:03.986723image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 2000000
20.0%
L 1000000
10.0%
c 1000000
10.0%
a 1000000
10.0%
t 1000000
10.0%
i 1000000
10.0%
n 1000000
10.0%
1000000
10.0%
B 250262
 
2.5%
D 250007
 
2.5%
Other values (2) 499731
 
5.0%
ValueCountFrequency (%)
o 60000
20.0%
L 30000
10.0%
c 30000
10.0%
a 30000
10.0%
t 30000
10.0%
i 30000
10.0%
n 30000
10.0%
30000
10.0%
A 7580
 
2.5%
B 7569
 
2.5%
Other values (2) 14851
 
5.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 10000000
100.0%
ValueCountFrequency (%)
(unknown) 300000
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
o 2000000
20.0%
L 1000000
10.0%
c 1000000
10.0%
a 1000000
10.0%
t 1000000
10.0%
i 1000000
10.0%
n 1000000
10.0%
1000000
10.0%
B 250262
 
2.5%
D 250007
 
2.5%
Other values (2) 499731
 
5.0%
ValueCountFrequency (%)
o 60000
20.0%
L 30000
10.0%
c 30000
10.0%
a 30000
10.0%
t 30000
10.0%
i 30000
10.0%
n 30000
10.0%
30000
10.0%
A 7580
 
2.5%
B 7569
 
2.5%
Other values (2) 14851
 
5.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 10000000
100.0%
ValueCountFrequency (%)
(unknown) 300000
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
o 2000000
20.0%
L 1000000
10.0%
c 1000000
10.0%
a 1000000
10.0%
t 1000000
10.0%
i 1000000
10.0%
n 1000000
10.0%
1000000
10.0%
B 250262
 
2.5%
D 250007
 
2.5%
Other values (2) 499731
 
5.0%
ValueCountFrequency (%)
o 60000
20.0%
L 30000
10.0%
c 30000
10.0%
a 30000
10.0%
t 30000
10.0%
i 30000
10.0%
n 30000
10.0%
30000
10.0%
A 7580
 
2.5%
B 7569
 
2.5%
Other values (2) 14851
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 10000000
100.0%
ValueCountFrequency (%)
(unknown) 300000
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
o 2000000
20.0%
L 1000000
10.0%
c 1000000
10.0%
a 1000000
10.0%
t 1000000
10.0%
i 1000000
10.0%
n 1000000
10.0%
1000000
10.0%
B 250262
 
2.5%
D 250007
 
2.5%
Other values (2) 499731
 
5.0%
ValueCountFrequency (%)
o 60000
20.0%
L 30000
10.0%
c 30000
10.0%
a 30000
10.0%
t 30000
10.0%
i 30000
10.0%
n 30000
10.0%
30000
10.0%
A 7580
 
2.5%
B 7569
 
2.5%
Other values (2) 14851
 
5.0%

online_purchases
Real number (ℝ)

 Full DatasetSystematic Sample
Distinct100100
Distinct (%)< 0.1%0.3%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean49.44601849.18843333
 Full DatasetSystematic Sample
Minimum00
Maximum9999
Zeros9997298
Zeros (%)1.0%1.0%
Negative00
Negative (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T02:08:04.550913image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Full DatasetSystematic Sample
Minimum00
5-th percentile44
Q12424
median4949
Q37474
95-th percentile9494
Maximum9999
Range9999
Interquartile range (IQR)5050

Descriptive statistics

 Full DatasetSystematic Sample
Standard deviation28.8614391328.91133668
Coefficient of variation (CV)0.58369592340.5877669752
Kurtosis-1.200754846-1.207525653
Mean49.44601849.18843333
Median Absolute Deviation (MAD)2525
Skewness0.001434218540.01496678687
Sum494460181475653
Variance832.9826689835.8653884
MonotonicityNot monotonicNot monotonic
2025-06-06T02:08:04.762486image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4 10324
 
1.0%
28 10269
 
1.0%
40 10198
 
1.0%
67 10151
 
1.0%
76 10150
 
1.0%
61 10150
 
1.0%
52 10140
 
1.0%
88 10134
 
1.0%
43 10133
 
1.0%
45 10132
 
1.0%
Other values (90) 898219
89.8%
ValueCountFrequency (%)
32 339
 
1.1%
76 336
 
1.1%
27 335
 
1.1%
69 333
 
1.1%
49 332
 
1.1%
86 332
 
1.1%
68 329
 
1.1%
45 328
 
1.1%
17 327
 
1.1%
18 327
 
1.1%
Other values (90) 26682
88.9%
ValueCountFrequency (%)
0 9997
1.0%
1 10023
1.0%
2 9792
1.0%
3 10091
1.0%
4 10324
1.0%
ValueCountFrequency (%)
0 298
1.0%
1 292
1.0%
2 321
1.1%
3 276
0.9%
4 320
1.1%
ValueCountFrequency (%)
0 298
< 0.1%
1 292
< 0.1%
2 321
< 0.1%
3 276
< 0.1%
4 320
< 0.1%
ValueCountFrequency (%)
0 9997
33.3%
1 10023
33.4%
2 9792
32.6%
3 10091
33.6%
4 10324
34.4%

in_store_purchases
Real number (ℝ)

 Full DatasetSystematic Sample
Distinct100100
Distinct (%)< 0.1%0.3%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean49.48448649.34656667
 Full DatasetSystematic Sample
Minimum00
Maximum9999
Zeros10016317
Zeros (%)1.0%1.1%
Negative00
Negative (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T02:08:04.968369image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Full DatasetSystematic Sample
Minimum00
5-th percentile54
Q12424
median4949
Q37574
95-th percentile9595
Maximum9999
Range9999
Interquartile range (IQR)5150

Descriptive statistics

 Full DatasetSystematic Sample
Standard deviation28.8827117428.89541411
Coefficient of variation (CV)0.58367205720.5855607808
Kurtosis-1.20140369-1.202546777
Mean49.48448649.34656667
Median Absolute Deviation (MAD)2525
Skewness0.001590435670.009032009929
Sum494844861480397
Variance834.2110375834.9449564
MonotonicityNot monotonicNot monotonic
2025-06-06T02:08:05.194645image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
38 10264
 
1.0%
30 10186
 
1.0%
86 10183
 
1.0%
10 10180
 
1.0%
14 10171
 
1.0%
7 10166
 
1.0%
13 10164
 
1.0%
50 10151
 
1.0%
67 10141
 
1.0%
91 10131
 
1.0%
Other values (90) 898263
89.8%
ValueCountFrequency (%)
50 334
 
1.1%
79 333
 
1.1%
51 332
 
1.1%
76 330
 
1.1%
38 329
 
1.1%
10 327
 
1.1%
18 326
 
1.1%
62 325
 
1.1%
4 320
 
1.1%
36 320
 
1.1%
Other values (90) 26724
89.1%
ValueCountFrequency (%)
0 10016
1.0%
1 9978
1.0%
2 9953
1.0%
3 9965
1.0%
4 9926
1.0%
ValueCountFrequency (%)
0 317
1.1%
1 281
0.9%
2 301
1.0%
3 297
1.0%
4 320
1.1%
ValueCountFrequency (%)
0 317
< 0.1%
1 281
< 0.1%
2 301
< 0.1%
3 297
< 0.1%
4 320
< 0.1%
ValueCountFrequency (%)
0 10016
33.4%
1 9978
33.3%
2 9953
33.2%
3 9965
33.2%
4 9926
33.1%

avg_items_per_transaction
Real number (ℝ)

 Full DatasetSystematic Sample
Distinct901901
Distinct (%)0.1%3.0%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean5.503121875.518995667
 Full DatasetSystematic Sample
Minimum11
Maximum1010
Zeros00
Zeros (%)0.0%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T02:08:05.420115image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Full DatasetSystematic Sample
Minimum11
5-th percentile1.451.44
Q13.263.28
median5.55.54
Q37.757.76
95-th percentile9.559.55
Maximum1010
Range99
Interquartile range (IQR)4.494.48

Descriptive statistics

 Full DatasetSystematic Sample
Standard deviation2.5976612752.597740489
Coefficient of variation (CV)0.47203411730.4706908007
Kurtosis-1.199082145-1.197458824
Mean5.503121875.518995667
Median Absolute Deviation (MAD)2.252.24
Skewness-4.461054903 × 10-5-0.01353169941
Sum5503121.87165569.87
Variance6.7478440976.74825565
MonotonicityNot monotonicNot monotonic
2025-06-06T02:08:05.619530image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.49 1205
 
0.1%
5 1198
 
0.1%
3.94 1197
 
0.1%
6.41 1196
 
0.1%
2.82 1193
 
0.1%
8.41 1192
 
0.1%
9.69 1192
 
0.1%
4.29 1190
 
0.1%
4.35 1188
 
0.1%
6.14 1188
 
0.1%
Other values (891) 988061
98.8%
ValueCountFrequency (%)
2.36 52
 
0.2%
6.74 51
 
0.2%
7.48 51
 
0.2%
9 51
 
0.2%
4.7 49
 
0.2%
8.71 49
 
0.2%
8.74 49
 
0.2%
9.02 48
 
0.2%
5.67 48
 
0.2%
6.3 48
 
0.2%
Other values (891) 29504
98.3%
ValueCountFrequency (%)
1 514
0.1%
1.01 1135
0.1%
1.02 1105
0.1%
1.03 1122
0.1%
1.04 1067
0.1%
ValueCountFrequency (%)
1 10
 
< 0.1%
1.01 40
0.1%
1.02 32
0.1%
1.03 23
0.1%
1.04 25
0.1%
ValueCountFrequency (%)
1 10
 
< 0.1%
1.01 40
< 0.1%
1.02 32
< 0.1%
1.03 23
< 0.1%
1.04 25
< 0.1%
ValueCountFrequency (%)
1 514
1.7%
1.01 1135
3.8%
1.02 1105
3.7%
1.03 1122
3.7%
1.04 1067
3.6%

avg_transaction_value
Real number (ℝ)

 Full DatasetSystematic Sample
Distinct4900122388
Distinct (%)4.9%74.6%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean255.1157678255.481149
 Full DatasetSystematic Sample
Minimum1010.02
Maximum500500
Zeros00
Zeros (%)0.0%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T02:08:05.832462image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Full DatasetSystematic Sample
Minimum1010.02
5-th percentile34.5233.979
Q1132.51132.42
median255.23255.94
Q3377.67378.7525
95-th percentile475.36475.78
Maximum500500
Range490489.98
Interquartile range (IQR)245.16246.3325

Descriptive statistics

 Full DatasetSystematic Sample
Standard deviation141.4300141141.8474272
Coefficient of variation (CV)0.55437582430.5552168046
Kurtosis-1.200885422-1.20331159
Mean255.1157678255.481149
Median Absolute Deviation (MAD)122.58123.175
Skewness-0.001148163222-0.001707380871
Sum255115767.87664434.47
Variance20002.4488820120.6926
MonotonicityNot monotonicNot monotonic
2025-06-06T02:08:06.031517image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
362.11 43
 
< 0.1%
157.68 43
 
< 0.1%
86.72 42
 
< 0.1%
303.99 41
 
< 0.1%
193.66 41
 
< 0.1%
112.64 40
 
< 0.1%
342.26 40
 
< 0.1%
454.72 39
 
< 0.1%
64.18 39
 
< 0.1%
280.55 39
 
< 0.1%
Other values (48991) 999593
> 99.9%
ValueCountFrequency (%)
487.28 5
 
< 0.1%
489.95 5
 
< 0.1%
269.06 5
 
< 0.1%
47.07 5
 
< 0.1%
304.22 5
 
< 0.1%
415.71 5
 
< 0.1%
231.25 5
 
< 0.1%
242.37 5
 
< 0.1%
229.29 5
 
< 0.1%
158.25 5
 
< 0.1%
Other values (22378) 29950
99.8%
ValueCountFrequency (%)
10 8
 
< 0.1%
10.01 18
< 0.1%
10.02 17
< 0.1%
10.03 28
< 0.1%
10.04 24
< 0.1%
ValueCountFrequency (%)
10.02 1
 
< 0.1%
10.03 1
 
< 0.1%
10.05 1
 
< 0.1%
10.07 1
 
< 0.1%
10.08 3
< 0.1%
ValueCountFrequency (%)
10.02 1
 
< 0.1%
10.03 1
 
< 0.1%
10.05 1
 
< 0.1%
10.07 1
 
< 0.1%
10.08 3
< 0.1%
ValueCountFrequency (%)
10 8
 
< 0.1%
10.01 18
0.1%
10.02 17
0.1%
10.03 28
0.1%
10.04 24
0.1%

total_returned_items
Real number (ℝ)

 Full DatasetSystematic Sample
Distinct1010
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean4.4981424.504633333
 Full DatasetSystematic Sample
Minimum00
Maximum99
Zeros1000603043
Zeros (%)10.0%10.1%
Negative00
Negative (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T02:08:06.195172image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Full DatasetSystematic Sample
Minimum00
5-th percentile00
Q122
median45
Q377
95-th percentile99
Maximum99
Range99
Interquartile range (IQR)55

Descriptive statistics

 Full DatasetSystematic Sample
Standard deviation2.8728050412.878191793
Coefficient of variation (CV)0.63866481770.6389403044
Kurtosis-1.225109848-1.225473688
Mean4.4981424.504633333
Median Absolute Deviation (MAD)33
Skewness0.0007692254728-0.001610088949
Sum4498142135139
Variance8.2530088018.283987998
MonotonicityNot monotonicNot monotonic
2025-06-06T02:08:06.308817image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
1 100298
10.0%
7 100190
10.0%
3 100119
10.0%
0 100060
10.0%
6 100004
10.0%
2 99991
10.0%
9 99942
10.0%
8 99838
10.0%
4 99821
10.0%
5 99737
10.0%
ValueCountFrequency (%)
9 3045
10.2%
0 3043
10.1%
3 3021
10.1%
6 3016
10.1%
8 3006
10.0%
2 3003
10.0%
5 2991
10.0%
4 2969
9.9%
7 2964
9.9%
1 2942
9.8%
ValueCountFrequency (%)
0 100060
10.0%
1 100298
10.0%
2 99991
10.0%
3 100119
10.0%
4 99821
10.0%
ValueCountFrequency (%)
0 3043
10.1%
1 2942
9.8%
2 3003
10.0%
3 3021
10.1%
4 2969
9.9%
ValueCountFrequency (%)
0 3043
0.3%
1 2942
0.3%
2 3003
0.3%
3 3021
0.3%
4 2969
0.3%
ValueCountFrequency (%)
0 100060
333.5%
1 100298
334.3%
2 99991
333.3%
3 100119
333.7%
4 99821
332.7%

total_returned_value
Real number (ℝ)

 Full DatasetSystematic Sample
Distinct9999926021
Distinct (%)10.0%86.7%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean500.3878374501.730237
 Full DatasetSystematic Sample
Minimum00.01
Maximum1000999.99
Zeros40
Zeros (%)< 0.1%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T02:08:06.502708image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Full DatasetSystematic Sample
Minimum00.01
5-th percentile5052.979
Q1250.63253.8725
median500.4501.7
Q3750.39748.98
95-th percentile950.22949.2215
Maximum1000999.99
Range1000999.98
Interquartile range (IQR)499.76495.1075

Descriptive statistics

 Full DatasetSystematic Sample
Standard deviation288.7174763287.2884784
Coefficient of variation (CV)0.57698739810.5725955049
Kurtosis-1.199754459-1.188818796
Mean500.3878374501.730237
Median Absolute Deviation (MAD)249.89247.65
Skewness-0.001264828821-0.002747522577
Sum500387837.415051907.11
Variance83357.7811582534.66982
MonotonicityNot monotonicNot monotonic
2025-06-06T02:08:06.701955image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
160.66 28
 
< 0.1%
467.66 26
 
< 0.1%
188.3 26
 
< 0.1%
488.88 25
 
< 0.1%
544.94 25
 
< 0.1%
651.87 25
 
< 0.1%
981.42 25
 
< 0.1%
330.91 25
 
< 0.1%
676.05 25
 
< 0.1%
227.59 25
 
< 0.1%
Other values (99989) 999745
> 99.9%
ValueCountFrequency (%)
514.02 5
 
< 0.1%
714.49 5
 
< 0.1%
928.66 4
 
< 0.1%
973.06 4
 
< 0.1%
139.72 4
 
< 0.1%
937.33 4
 
< 0.1%
198.43 4
 
< 0.1%
577.78 4
 
< 0.1%
866.57 4
 
< 0.1%
281.52 4
 
< 0.1%
Other values (26011) 29958
99.9%
ValueCountFrequency (%)
0 4
 
< 0.1%
0.01 13
< 0.1%
0.02 12
< 0.1%
0.03 11
< 0.1%
0.04 7
< 0.1%
ValueCountFrequency (%)
0.01 1
< 0.1%
0.02 1
< 0.1%
0.04 1
< 0.1%
0.11 1
< 0.1%
0.17 1
< 0.1%
ValueCountFrequency (%)
0.01 1
< 0.1%
0.02 1
< 0.1%
0.04 1
< 0.1%
0.11 1
< 0.1%
0.17 1
< 0.1%
ValueCountFrequency (%)
0 4
 
< 0.1%
0.01 13
< 0.1%
0.02 12
< 0.1%
0.03 11
< 0.1%
0.04 7
< 0.1%

total_sales
Real number (ℝ)

 Full DatasetSystematic Sample
Distinct62925429563
Distinct (%)62.9%98.5%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean5056.0597655070.517322
 Full DatasetSystematic Sample
Minimum100.01100.04
Maximum9999.989998.05
Zeros00
Zeros (%)0.0%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T02:08:06.912971image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Full DatasetSystematic Sample
Minimum100.01100.04
5-th percentile595.7095581.918
Q12577.86752552.5375
median5059.6955102.03
Q37534.80257586.2775
95-th percentile9507.969522.561
Maximum9999.989998.05
Range9899.979898.01
Interquartile range (IQR)4956.9355033.74

Descriptive statistics

 Full DatasetSystematic Sample
Standard deviation2859.1000582876.151961
Coefficient of variation (CV)0.56547987770.5672304774
Kurtosis-1.201132214-1.219650902
Mean5056.0597655070.517322
Median Absolute Deviation (MAD)2478.3652517.305
Skewness-0.002792355347-0.009818384845
Sum5056059765152115519.7
Variance8174453.148272250.103
MonotonicityNot monotonicNot monotonic
2025-06-06T02:08:07.121155image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
9263.29 8
 
< 0.1%
1070.51 8
 
< 0.1%
8973.11 8
 
< 0.1%
7882.97 8
 
< 0.1%
630.03 8
 
< 0.1%
8669.59 8
 
< 0.1%
8191.02 8
 
< 0.1%
2558.91 8
 
< 0.1%
5572.95 8
 
< 0.1%
8266.95 8
 
< 0.1%
Other values (629244) 999920
> 99.9%
ValueCountFrequency (%)
5573.97 3
 
< 0.1%
6929.76 2
 
< 0.1%
4310.88 2
 
< 0.1%
1790.99 2
 
< 0.1%
4228.4 2
 
< 0.1%
8710.53 2
 
< 0.1%
7292.92 2
 
< 0.1%
3642.88 2
 
< 0.1%
5923.6 2
 
< 0.1%
2068.75 2
 
< 0.1%
Other values (29553) 29979
99.9%
ValueCountFrequency (%)
100.01 2
< 0.1%
100.02 2
< 0.1%
100.04 2
< 0.1%
100.05 2
< 0.1%
100.06 3
< 0.1%
ValueCountFrequency (%)
100.04 1
< 0.1%
100.06 2
< 0.1%
100.32 1
< 0.1%
100.36 1
< 0.1%
100.42 1
< 0.1%
ValueCountFrequency (%)
100.04 1
< 0.1%
100.06 2
< 0.1%
100.32 1
< 0.1%
100.36 1
< 0.1%
100.42 1
< 0.1%
ValueCountFrequency (%)
100.01 2
< 0.1%
100.02 2
< 0.1%
100.04 2
< 0.1%
100.05 2
< 0.1%
100.06 3
< 0.1%

total_transactions
Real number (ℝ)

 Full DatasetSystematic Sample
Distinct9999
Distinct (%)< 0.1%0.3%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean49.98738649.87116667
 Full DatasetSystematic Sample
Minimum11
Maximum9999
Zeros00
Zeros (%)0.0%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T02:08:07.342493image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Full DatasetSystematic Sample
Minimum11
5-th percentile55
Q12525
median5050
Q37575
95-th percentile9594
Maximum9999
Range9898
Interquartile range (IQR)5050

Descriptive statistics

 Full DatasetSystematic Sample
Standard deviation28.5716889528.58786358
Coefficient of variation (CV)0.57157797660.5732343054
Kurtosis-1.200697232-1.197065103
Mean49.98738649.87116667
Median Absolute Deviation (MAD)2525
Skewness6.496950968 × 10-5-0.000849598413
Sum499873861496135
Variance816.3414092817.2659442
MonotonicityNot monotonicNot monotonic
2025-06-06T02:08:07.569852image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
93 10385
 
1.0%
24 10328
 
1.0%
61 10316
 
1.0%
70 10306
 
1.0%
49 10290
 
1.0%
14 10280
 
1.0%
83 10278
 
1.0%
27 10251
 
1.0%
16 10247
 
1.0%
75 10245
 
1.0%
Other values (89) 897074
89.7%
ValueCountFrequency (%)
57 342
 
1.1%
86 339
 
1.1%
94 335
 
1.1%
35 335
 
1.1%
5 333
 
1.1%
4 331
 
1.1%
25 329
 
1.1%
50 329
 
1.1%
28 327
 
1.1%
88 326
 
1.1%
Other values (89) 26674
88.9%
ValueCountFrequency (%)
1 10053
1.0%
2 10174
1.0%
3 10113
1.0%
4 10133
1.0%
5 10140
1.0%
ValueCountFrequency (%)
1 323
1.1%
2 298
1.0%
3 308
1.0%
4 331
1.1%
5 333
1.1%
ValueCountFrequency (%)
1 323
< 0.1%
2 298
< 0.1%
3 308
< 0.1%
4 331
< 0.1%
5 333
< 0.1%
ValueCountFrequency (%)
1 10053
33.5%
2 10174
33.9%
3 10113
33.7%
4 10133
33.8%
5 10140
33.8%

total_items_purchased
Real number (ℝ)

 Full DatasetSystematic Sample
Distinct499499
Distinct (%)< 0.1%1.7%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean250.042763249.4003667
 Full DatasetSystematic Sample
Minimum11
Maximum499499
Zeros00
Zeros (%)0.0%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T02:08:07.774106image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Full DatasetSystematic Sample
Minimum11
5-th percentile2625
Q1125124
median250251
Q3375373
95-th percentile475474
Maximum499499
Range498498
Interquartile range (IQR)250249

Descriptive statistics

 Full DatasetSystematic Sample
Standard deviation143.9845462143.5749326
Coefficient of variation (CV)0.57583968620.5756805192
Kurtosis-1.199364571-1.195088792
Mean250.042763249.4003667
Median Absolute Deviation (MAD)125124
Skewness-0.0005289537985-0.003945628736
Sum2500427637482011
Variance20731.5495420613.76127
MonotonicityNot monotonicNot monotonic
2025-06-06T02:08:07.982753image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
282 2156
 
0.2%
285 2146
 
0.2%
355 2132
 
0.2%
459 2099
 
0.2%
296 2098
 
0.2%
241 2096
 
0.2%
413 2090
 
0.2%
331 2088
 
0.2%
425 2087
 
0.2%
260 2086
 
0.2%
Other values (489) 978922
97.9%
ValueCountFrequency (%)
432 84
 
0.3%
19 82
 
0.3%
27 81
 
0.3%
109 81
 
0.3%
446 78
 
0.3%
425 78
 
0.3%
117 78
 
0.3%
327 78
 
0.3%
312 78
 
0.3%
301 78
 
0.3%
Other values (489) 29204
97.3%
ValueCountFrequency (%)
1 2005
0.2%
2 2077
0.2%
3 1999
0.2%
4 2019
0.2%
5 1988
0.2%
ValueCountFrequency (%)
1 69
0.2%
2 53
0.2%
3 50
0.2%
4 61
0.2%
5 63
0.2%
ValueCountFrequency (%)
1 69
< 0.1%
2 53
< 0.1%
3 50
< 0.1%
4 61
< 0.1%
5 63
< 0.1%
ValueCountFrequency (%)
1 2005
6.7%
2 2077
6.9%
3 1999
6.7%
4 2019
6.7%
5 1988
6.6%

total_discounts_received
Real number (ℝ)

 Full DatasetSystematic Sample
Distinct9999525886
Distinct (%)10.0%86.3%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean499.6743882498.7390803
 Full DatasetSystematic Sample
Minimum00.01
Maximum1000999.98
Zeros60
Zeros (%)< 0.1%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T02:08:08.207457image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Full DatasetSystematic Sample
Minimum00.01
5-th percentile50.1650.268
Q1249.76251.03
median499.51496.145
Q3749.54749.735
95-th percentile949.66947.691
Maximum1000999.98
Range1000999.97
Interquartile range (IQR)499.78498.705

Descriptive statistics

 Full DatasetSystematic Sample
Standard deviation288.5791016288.1539788
Coefficient of variation (CV)0.57753430710.5777649882
Kurtosis-1.200167414-1.2000378
Mean499.6743882498.7390803
Median Absolute Deviation (MAD)249.9249.435
Skewness0.00097450105350.004135538111
Sum499674388.214962172.41
Variance83277.8978683032.71553
MonotonicityNot monotonicNot monotonic
2025-06-06T02:08:08.433358image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
52.87 26
 
< 0.1%
811.21 26
 
< 0.1%
721.58 26
 
< 0.1%
418.88 25
 
< 0.1%
760.97 25
 
< 0.1%
406.5 24
 
< 0.1%
784.58 24
 
< 0.1%
595.87 24
 
< 0.1%
918 24
 
< 0.1%
34.86 24
 
< 0.1%
Other values (99985) 999752
> 99.9%
ValueCountFrequency (%)
182.63 5
 
< 0.1%
61.51 5
 
< 0.1%
928.19 4
 
< 0.1%
394.34 4
 
< 0.1%
472.48 4
 
< 0.1%
427.73 4
 
< 0.1%
10.12 4
 
< 0.1%
705.39 4
 
< 0.1%
268.2 4
 
< 0.1%
98.15 4
 
< 0.1%
Other values (25876) 29958
99.9%
ValueCountFrequency (%)
0 6
< 0.1%
0.01 13
< 0.1%
0.02 8
< 0.1%
0.03 8
< 0.1%
0.04 6
< 0.1%
ValueCountFrequency (%)
0.01 1
< 0.1%
0.03 1
< 0.1%
0.05 1
< 0.1%
0.12 2
< 0.1%
0.13 1
< 0.1%
ValueCountFrequency (%)
0.01 1
< 0.1%
0.03 1
< 0.1%
0.05 1
< 0.1%
0.12 2
< 0.1%
0.13 1
< 0.1%
ValueCountFrequency (%)
0 6
< 0.1%
0.01 13
< 0.1%
0.02 8
< 0.1%
0.03 8
< 0.1%
0.04 6
< 0.1%

avg_spent_per_category
Real number (ℝ)

 Full DatasetSystematic Sample
Distinct9899925874
Distinct (%)9.9%86.2%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean505.1754779507.2349573
 Full DatasetSystematic Sample
Minimum1010.02
Maximum1000999.92
Zeros00
Zeros (%)0.0%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T02:08:08.638682image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Full DatasetSystematic Sample
Minimum1010.02
5-th percentile59.4959.169
Q1257.24259.7075
median505.14510.545
Q3753.06755.1775
95-th percentile950.7405949.5105
Maximum1000999.92
Range990989.9
Interquartile range (IQR)495.82495.47

Descriptive statistics

 Full DatasetSystematic Sample
Standard deviation286.0591784286.5485484
Coefficient of variation (CV)0.5662570550.5649227134
Kurtosis-1.201963641-1.203596811
Mean505.1754779507.2349573
Median Absolute Deviation (MAD)247.91247.71
Skewness-0.0002454959133-0.02254511471
Sum505175477.915217048.72
Variance81829.8535582110.07062
MonotonicityNot monotonicNot monotonic
2025-06-06T02:08:08.835682image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
202.69 27
 
< 0.1%
969.16 26
 
< 0.1%
582.24 26
 
< 0.1%
806.1 25
 
< 0.1%
330.74 25
 
< 0.1%
798.54 25
 
< 0.1%
299.29 25
 
< 0.1%
312.38 25
 
< 0.1%
825.53 24
 
< 0.1%
525.28 24
 
< 0.1%
Other values (98989) 999748
> 99.9%
ValueCountFrequency (%)
141.03 5
 
< 0.1%
36.15 4
 
< 0.1%
548.8 4
 
< 0.1%
710.93 4
 
< 0.1%
319.46 4
 
< 0.1%
333.34 4
 
< 0.1%
574.26 4
 
< 0.1%
665.71 4
 
< 0.1%
992.05 4
 
< 0.1%
514.73 4
 
< 0.1%
Other values (25864) 29959
99.9%
ValueCountFrequency (%)
10 4
 
< 0.1%
10.01 8
< 0.1%
10.02 13
< 0.1%
10.03 10
< 0.1%
10.04 13
< 0.1%
ValueCountFrequency (%)
10.02 1
< 0.1%
10.03 1
< 0.1%
10.05 2
< 0.1%
10.06 2
< 0.1%
10.1 1
< 0.1%
ValueCountFrequency (%)
10.02 1
< 0.1%
10.03 1
< 0.1%
10.05 2
< 0.1%
10.06 2
< 0.1%
10.1 1
< 0.1%
ValueCountFrequency (%)
10 4
 
< 0.1%
10.01 8
< 0.1%
10.02 13
< 0.1%
10.03 10
< 0.1%
10.04 13
< 0.1%

max_single_purchase_value
Real number (ℝ)

 Full DatasetSystematic Sample
Distinct9900125794
Distinct (%)9.9%86.0%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean505.0014045504.4945963
 Full DatasetSystematic Sample
Minimum1010.02
Maximum1000999.99
Zeros00
Zeros (%)0.0%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T02:08:09.059522image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Full DatasetSystematic Sample
Minimum1010.02
5-th percentile59.358.23
Q1256.84255.115
median505.22506.13
Q3753.21752.72
95-th percentile950.55951.5725
Maximum1000999.99
Range990989.97
Interquartile range (IQR)496.37497.605

Descriptive statistics

 Full DatasetSystematic Sample
Standard deviation286.0733241286.2036938
Coefficient of variation (CV)0.56648025450.5673077489
Kurtosis-1.202495075-1.198648107
Mean505.0014045504.4945963
Median Absolute Deviation (MAD)248.18248.68
Skewness-0.0008466890807-0.0007518293936
Sum505001404.515134837.89
Variance81837.9467781912.55434
MonotonicityNot monotonicNot monotonic
2025-06-06T02:08:09.766111image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
575.57 28
 
< 0.1%
461.6 26
 
< 0.1%
874.29 25
 
< 0.1%
105.78 25
 
< 0.1%
354.85 25
 
< 0.1%
736.87 25
 
< 0.1%
439.72 25
 
< 0.1%
893.75 24
 
< 0.1%
179.32 24
 
< 0.1%
330.94 24
 
< 0.1%
Other values (98991) 999749
> 99.9%
ValueCountFrequency (%)
157.57 5
 
< 0.1%
985.66 4
 
< 0.1%
661.26 4
 
< 0.1%
621.57 4
 
< 0.1%
970.54 4
 
< 0.1%
139.51 4
 
< 0.1%
477.98 4
 
< 0.1%
701.49 4
 
< 0.1%
452.59 4
 
< 0.1%
846.64 4
 
< 0.1%
Other values (25784) 29959
99.9%
ValueCountFrequency (%)
10 6
 
< 0.1%
10.01 8
< 0.1%
10.02 15
< 0.1%
10.03 5
 
< 0.1%
10.04 15
< 0.1%
ValueCountFrequency (%)
10.02 1
< 0.1%
10.08 1
< 0.1%
10.11 1
< 0.1%
10.16 1
< 0.1%
10.17 1
< 0.1%
ValueCountFrequency (%)
10.02 1
< 0.1%
10.08 1
< 0.1%
10.11 1
< 0.1%
10.16 1
< 0.1%
10.17 1
< 0.1%
ValueCountFrequency (%)
10 6
 
< 0.1%
10.01 8
< 0.1%
10.02 15
0.1%
10.03 5
 
< 0.1%
10.04 15
0.1%

min_single_purchase_value
Real number (ℝ)

 Full DatasetSystematic Sample
Distinct991991
Distinct (%)0.1%3.3%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean5.043848965.012402
 Full DatasetSystematic Sample
Minimum0.10.1
Maximum1010
Zeros00
Zeros (%)0.0%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T02:08:09.969603image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Full DatasetSystematic Sample
Minimum0.10.1
5-th percentile0.590.57
Q12.572.53
median5.045.01
Q37.517.48
95-th percentile9.59.52
Maximum1010
Range9.99.9
Interquartile range (IQR)4.944.95

Descriptive statistics

 Full DatasetSystematic Sample
Standard deviation2.8559046442.856644035
Coefficient of variation (CV)0.5662153380.5699151894
Kurtosis-1.198193882-1.191228918
Mean5.043848965.012402
Median Absolute Deviation (MAD)2.472.48
Skewness0.0024154035070.01785919507
Sum5043848.96150372.06
Variance8.1561913358.160415144
MonotonicityNot monotonicNot monotonic
2025-06-06T02:08:10.174356image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4.66 1123
 
0.1%
0.29 1112
 
0.1%
3.05 1110
 
0.1%
1.67 1101
 
0.1%
4.67 1092
 
0.1%
6.93 1092
 
0.1%
6.14 1091
 
0.1%
5.19 1091
 
0.1%
5.31 1086
 
0.1%
5.02 1086
 
0.1%
Other values (981) 989016
98.9%
ValueCountFrequency (%)
3.88 53
 
0.2%
9.99 49
 
0.2%
2.27 49
 
0.2%
2.65 47
 
0.2%
3.84 47
 
0.2%
1.72 47
 
0.2%
1.74 46
 
0.2%
3.25 46
 
0.2%
0.34 45
 
0.1%
9.92 45
 
0.1%
Other values (981) 29526
98.4%
ValueCountFrequency (%)
0.1 491
< 0.1%
0.11 1041
0.1%
0.12 1011
0.1%
0.13 1044
0.1%
0.14 1013
0.1%
ValueCountFrequency (%)
0.1 8
 
< 0.1%
0.11 32
0.1%
0.12 32
0.1%
0.13 40
0.1%
0.14 37
0.1%
ValueCountFrequency (%)
0.1 8
 
< 0.1%
0.11 32
< 0.1%
0.12 32
< 0.1%
0.13 40
< 0.1%
0.14 37
< 0.1%
ValueCountFrequency (%)
0.1 491
1.6%
0.11 1041
3.5%
0.12 1011
3.4%
0.13 1044
3.5%
0.14 1013
3.4%

product_name
['Text', 'Text']

 Full DatasetSystematic Sample
Distinct44
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T02:08:10.435008image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

 Full DatasetSystematic Sample
Max length99
Median length99
Mean length99
Min length99

Characters and Unicode

 Full DatasetSystematic Sample
Total characters9000000270000
Distinct characters1212
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Full DatasetSystematic Sample
Unique00 ?
Unique (%)0.0%0.0%

Sample

 Full DatasetSystematic Sample
1st rowProduct DProduct D
2nd rowProduct CProduct A
3rd rowProduct BProduct B
4th rowProduct AProduct B
5th rowProduct CProduct A
ValueCountFrequency (%)
product 1000000
50.0%
b 250375
 
12.5%
c 249957
 
12.5%
a 249928
 
12.5%
d 249740
 
12.5%
ValueCountFrequency (%)
product 30000
50.0%
a 7665
 
12.8%
b 7481
 
12.5%
c 7442
 
12.4%
d 7412
 
12.4%
2025-06-06T02:08:10.751608image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
P 1000000
11.1%
r 1000000
11.1%
o 1000000
11.1%
d 1000000
11.1%
u 1000000
11.1%
c 1000000
11.1%
t 1000000
11.1%
1000000
11.1%
B 250375
 
2.8%
C 249957
 
2.8%
Other values (2) 499668
5.6%
ValueCountFrequency (%)
P 30000
11.1%
r 30000
11.1%
o 30000
11.1%
d 30000
11.1%
u 30000
11.1%
c 30000
11.1%
t 30000
11.1%
30000
11.1%
A 7665
 
2.8%
B 7481
 
2.8%
Other values (2) 14854
5.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 9000000
100.0%
ValueCountFrequency (%)
(unknown) 270000
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
P 1000000
11.1%
r 1000000
11.1%
o 1000000
11.1%
d 1000000
11.1%
u 1000000
11.1%
c 1000000
11.1%
t 1000000
11.1%
1000000
11.1%
B 250375
 
2.8%
C 249957
 
2.8%
Other values (2) 499668
5.6%
ValueCountFrequency (%)
P 30000
11.1%
r 30000
11.1%
o 30000
11.1%
d 30000
11.1%
u 30000
11.1%
c 30000
11.1%
t 30000
11.1%
30000
11.1%
A 7665
 
2.8%
B 7481
 
2.8%
Other values (2) 14854
5.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 9000000
100.0%
ValueCountFrequency (%)
(unknown) 270000
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
P 1000000
11.1%
r 1000000
11.1%
o 1000000
11.1%
d 1000000
11.1%
u 1000000
11.1%
c 1000000
11.1%
t 1000000
11.1%
1000000
11.1%
B 250375
 
2.8%
C 249957
 
2.8%
Other values (2) 499668
5.6%
ValueCountFrequency (%)
P 30000
11.1%
r 30000
11.1%
o 30000
11.1%
d 30000
11.1%
u 30000
11.1%
c 30000
11.1%
t 30000
11.1%
30000
11.1%
A 7665
 
2.8%
B 7481
 
2.8%
Other values (2) 14854
5.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 9000000
100.0%
ValueCountFrequency (%)
(unknown) 270000
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
P 1000000
11.1%
r 1000000
11.1%
o 1000000
11.1%
d 1000000
11.1%
u 1000000
11.1%
c 1000000
11.1%
t 1000000
11.1%
1000000
11.1%
B 250375
 
2.8%
C 249957
 
2.8%
Other values (2) 499668
5.6%
ValueCountFrequency (%)
P 30000
11.1%
r 30000
11.1%
o 30000
11.1%
d 30000
11.1%
u 30000
11.1%
c 30000
11.1%
t 30000
11.1%
30000
11.1%
A 7665
 
2.8%
B 7481
 
2.8%
Other values (2) 14854
5.5%

product_brand
['Text', 'Text']

 Full DatasetSystematic Sample
Distinct33
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T02:08:10.905392image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

 Full DatasetSystematic Sample
Max length77
Median length77
Mean length77
Min length77

Characters and Unicode

 Full DatasetSystematic Sample
Total characters7000000210000
Distinct characters99
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Full DatasetSystematic Sample
Unique00 ?
Unique (%)0.0%0.0%

Sample

 Full DatasetSystematic Sample
1st rowBrand YBrand Y
2nd rowBrand XBrand X
3rd rowBrand XBrand Z
4th rowBrand ZBrand Y
5th rowBrand XBrand X
ValueCountFrequency (%)
brand 1000000
50.0%
y 333775
 
16.7%
z 333608
 
16.7%
x 332617
 
16.6%
ValueCountFrequency (%)
brand 30000
50.0%
y 10245
 
17.1%
x 9890
 
16.5%
z 9865
 
16.4%
2025-06-06T02:08:11.155148image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
B 1000000
14.3%
r 1000000
14.3%
a 1000000
14.3%
n 1000000
14.3%
d 1000000
14.3%
1000000
14.3%
Y 333775
 
4.8%
Z 333608
 
4.8%
X 332617
 
4.8%
ValueCountFrequency (%)
B 30000
14.3%
r 30000
14.3%
a 30000
14.3%
n 30000
14.3%
d 30000
14.3%
30000
14.3%
Y 10245
 
4.9%
X 9890
 
4.7%
Z 9865
 
4.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 7000000
100.0%
ValueCountFrequency (%)
(unknown) 210000
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
B 1000000
14.3%
r 1000000
14.3%
a 1000000
14.3%
n 1000000
14.3%
d 1000000
14.3%
1000000
14.3%
Y 333775
 
4.8%
Z 333608
 
4.8%
X 332617
 
4.8%
ValueCountFrequency (%)
B 30000
14.3%
r 30000
14.3%
a 30000
14.3%
n 30000
14.3%
d 30000
14.3%
30000
14.3%
Y 10245
 
4.9%
X 9890
 
4.7%
Z 9865
 
4.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 7000000
100.0%
ValueCountFrequency (%)
(unknown) 210000
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
B 1000000
14.3%
r 1000000
14.3%
a 1000000
14.3%
n 1000000
14.3%
d 1000000
14.3%
1000000
14.3%
Y 333775
 
4.8%
Z 333608
 
4.8%
X 332617
 
4.8%
ValueCountFrequency (%)
B 30000
14.3%
r 30000
14.3%
a 30000
14.3%
n 30000
14.3%
d 30000
14.3%
30000
14.3%
Y 10245
 
4.9%
X 9890
 
4.7%
Z 9865
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 7000000
100.0%
ValueCountFrequency (%)
(unknown) 210000
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
B 1000000
14.3%
r 1000000
14.3%
a 1000000
14.3%
n 1000000
14.3%
d 1000000
14.3%
1000000
14.3%
Y 333775
 
4.8%
Z 333608
 
4.8%
X 332617
 
4.8%
ValueCountFrequency (%)
B 30000
14.3%
r 30000
14.3%
a 30000
14.3%
n 30000
14.3%
d 30000
14.3%
30000
14.3%
Y 10245
 
4.9%
X 9890
 
4.7%
Z 9865
 
4.7%

product_rating
Real number (ℝ)

 Full DatasetSystematic Sample
Distinct4141
Distinct (%)< 0.1%0.1%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean2.99900963.000233333
 Full DatasetSystematic Sample
Minimum11
Maximum55
Zeros00
Zeros (%)0.0%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T02:08:11.315195image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Full DatasetSystematic Sample
Minimum11
5-th percentile1.21.2
Q122
median33
Q344
95-th percentile4.84.8
Maximum55
Range44
Interquartile range (IQR)22

Descriptive statistics

 Full DatasetSystematic Sample
Standard deviation1.1548006031.155675473
Coefficient of variation (CV)0.38506065570.385195198
Kurtosis-1.196293362-1.194473672
Mean2.99900963.000233333
Median Absolute Deviation (MAD)11
Skewness-0.0005343871929-0.0009974057543
Sum2999009.690007
Variance1.3335644331.335585798
MonotonicityNot monotonicNot monotonic
2025-06-06T02:08:11.527832image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
2.9 25242
 
2.5%
3.4 25229
 
2.5%
2.6 25229
 
2.5%
1.3 25194
 
2.5%
3 25181
 
2.5%
4.7 25166
 
2.5%
4.3 25159
 
2.5%
4.1 25146
 
2.5%
1.6 25141
 
2.5%
4 25134
 
2.5%
Other values (31) 748179
74.8%
ValueCountFrequency (%)
4.9 809
 
2.7%
3.4 806
 
2.7%
4.7 790
 
2.6%
1.5 790
 
2.6%
3 785
 
2.6%
3.7 780
 
2.6%
3.6 779
 
2.6%
2.9 775
 
2.6%
1.2 766
 
2.6%
4.5 766
 
2.6%
Other values (31) 22154
73.8%
ValueCountFrequency (%)
1 12653
1.3%
1.1 24871
2.5%
1.2 25095
2.5%
1.3 25194
2.5%
1.4 24848
2.5%
ValueCountFrequency (%)
1 370
1.2%
1.1 741
2.5%
1.2 766
2.6%
1.3 756
2.5%
1.4 760
2.5%
ValueCountFrequency (%)
1 370
< 0.1%
1.1 741
0.1%
1.2 766
0.1%
1.3 756
0.1%
1.4 760
0.1%
ValueCountFrequency (%)
1 12653
42.2%
1.1 24871
82.9%
1.2 25095
83.7%
1.3 25194
84.0%
1.4 24848
82.8%

product_review_count
Real number (ℝ)

 Full DatasetSystematic Sample
Distinct10001000
Distinct (%)0.1%3.3%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean499.235198499.7586667
 Full DatasetSystematic Sample
Minimum00
Maximum999999
Zeros98726
Zeros (%)0.1%0.1%
Negative00
Negative (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T02:08:11.749427image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Full DatasetSystematic Sample
Minimum00
5-th percentile5052
Q1250250
median499499
Q3749751
95-th percentile949952.05
Maximum999999
Range999999
Interquartile range (IQR)499501

Descriptive statistics

 Full DatasetSystematic Sample
Standard deviation288.4461496288.5432539
Coefficient of variation (CV)0.57777606780.5773651828
Kurtosis-1.19905271-1.1968163
Mean499.235198499.7586667
Median Absolute Deviation (MAD)250250
Skewness0.0011900144960.008804364011
Sum49923519814992760
Variance83201.1812283257.2094
MonotonicityNot monotonicNot monotonic
2025-06-06T02:08:11.954883image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
974 1095
 
0.1%
56 1089
 
0.1%
769 1089
 
0.1%
725 1088
 
0.1%
683 1085
 
0.1%
229 1082
 
0.1%
501 1079
 
0.1%
937 1074
 
0.1%
384 1073
 
0.1%
497 1072
 
0.1%
Other values (990) 989174
98.9%
ValueCountFrequency (%)
333 51
 
0.2%
672 48
 
0.2%
769 47
 
0.2%
580 47
 
0.2%
220 46
 
0.2%
833 45
 
0.1%
559 44
 
0.1%
638 44
 
0.1%
869 44
 
0.1%
119 44
 
0.1%
Other values (990) 29540
98.5%
ValueCountFrequency (%)
0 987
0.1%
1 999
0.1%
2 1006
0.1%
3 1006
0.1%
4 1027
0.1%
ValueCountFrequency (%)
0 26
0.1%
1 34
0.1%
2 26
0.1%
3 41
0.1%
4 18
0.1%
ValueCountFrequency (%)
0 26
< 0.1%
1 34
< 0.1%
2 26
< 0.1%
3 41
< 0.1%
4 18
< 0.1%
ValueCountFrequency (%)
0 987
3.3%
1 999
3.3%
2 1006
3.4%
3 1006
3.4%
4 1027
3.4%

product_stock
Real number (ℝ)

 Full DatasetSystematic Sample
Distinct100100
Distinct (%)< 0.1%0.3%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean49.51512949.78733333
 Full DatasetSystematic Sample
Minimum00
Maximum9999
Zeros10174289
Zeros (%)1.0%1.0%
Negative00
Negative (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T02:08:12.161514image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Full DatasetSystematic Sample
Minimum00
5-th percentile55
Q12525
median4950
Q37575
95-th percentile9595
Maximum9999
Range9999
Interquartile range (IQR)5050

Descriptive statistics

 Full DatasetSystematic Sample
Standard deviation28.8766452928.98851929
Coefficient of variation (CV)0.58318832790.5822468759
Kurtosis-1.200520476-1.209739776
Mean49.51512949.78733333
Median Absolute Deviation (MAD)2525
Skewness0.0006383736941-0.01261429473
Sum495151291493620
Variance833.860643840.3342507
MonotonicityNot monotonicNot monotonic
2025-06-06T02:08:12.399310image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
89 10261
 
1.0%
70 10245
 
1.0%
60 10187
 
1.0%
23 10175
 
1.0%
0 10174
 
1.0%
54 10171
 
1.0%
44 10148
 
1.0%
96 10147
 
1.0%
32 10138
 
1.0%
77 10136
 
1.0%
Other values (90) 898218
89.8%
ValueCountFrequency (%)
89 344
 
1.1%
52 336
 
1.1%
59 333
 
1.1%
83 330
 
1.1%
78 329
 
1.1%
70 329
 
1.1%
98 328
 
1.1%
12 326
 
1.1%
82 324
 
1.1%
27 324
 
1.1%
Other values (90) 26697
89.0%
ValueCountFrequency (%)
0 10174
1.0%
1 9857
1.0%
2 9895
1.0%
3 10030
1.0%
4 9924
1.0%
ValueCountFrequency (%)
0 289
1.0%
1 274
0.9%
2 308
1.0%
3 316
1.1%
4 297
1.0%
ValueCountFrequency (%)
0 289
< 0.1%
1 274
< 0.1%
2 308
< 0.1%
3 316
< 0.1%
4 297
< 0.1%
ValueCountFrequency (%)
0 10174
33.9%
1 9857
32.9%
2 9895
33.0%
3 10030
33.4%
4 9924
33.1%

product_return_rate
Real number (ℝ)

 Full DatasetSystematic Sample
Distinct5151
Distinct (%)< 0.1%0.2%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean0.250137410.2512543333
 Full DatasetSystematic Sample
Minimum00
Maximum0.50.5
Zeros9960315
Zeros (%)1.0%1.1%
Negative00
Negative (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T02:08:12.672169image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Full DatasetSystematic Sample
Minimum00
5-th percentile0.030.02
Q10.130.13
median0.250.25
Q30.380.38
95-th percentile0.480.48
Maximum0.50.5
Range0.50.5
Interquartile range (IQR)0.250.25

Descriptive statistics

 Full DatasetSystematic Sample
Standard deviation0.14440848960.1451581402
Coefficient of variation (CV)0.57731664210.5777338775
Kurtosis-1.197824771-1.207624816
Mean0.250137410.2512543333
Median Absolute Deviation (MAD)0.130.13
Skewness-0.0005165569762-0.007170390778
Sum250137.417537.63
Variance0.020853811870.02107088568
MonotonicityNot monotonicNot monotonic
2025-06-06T02:08:13.003757image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.43 20287
 
2.0%
0.38 20282
 
2.0%
0.03 20242
 
2.0%
0.46 20215
 
2.0%
0.4 20209
 
2.0%
0.14 20164
 
2.0%
0.45 20148
 
2.0%
0.16 20140
 
2.0%
0.06 20135
 
2.0%
0.29 20118
 
2.0%
Other values (41) 798060
79.8%
ValueCountFrequency (%)
0.4 676
 
2.3%
0.46 668
 
2.2%
0.45 633
 
2.1%
0.27 632
 
2.1%
0.21 631
 
2.1%
0.49 631
 
2.1%
0.43 630
 
2.1%
0.14 628
 
2.1%
0.19 626
 
2.1%
0.48 626
 
2.1%
Other values (41) 23619
78.7%
ValueCountFrequency (%)
0 9960
1.0%
0.01 19921
2.0%
0.02 19994
2.0%
0.03 20242
2.0%
0.04 19825
2.0%
ValueCountFrequency (%)
0 315
1.1%
0.01 594
2.0%
0.02 610
2.0%
0.03 609
2.0%
0.04 604
2.0%
ValueCountFrequency (%)
0 315
< 0.1%
0.01 594
0.1%
0.02 610
0.1%
0.03 609
0.1%
0.04 604
0.1%
ValueCountFrequency (%)
0 9960
33.2%
0.01 19921
66.4%
0.02 19994
66.6%
0.03 20242
67.5%
0.04 19825
66.1%

product_size
['Text', 'Text']

 Full DatasetSystematic Sample
Distinct33
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T02:08:13.337107image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

 Full DatasetSystematic Sample
Max length66
Median length55
Mean length5.3335015.3283
Min length55

Characters and Unicode

 Full DatasetSystematic Sample
Total characters5333501159849
Distinct characters1212
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Full DatasetSystematic Sample
Unique00 ?
Unique (%)0.0%0.0%

Sample

 Full DatasetSystematic Sample
1st rowSmallSmall
2nd rowMediumMedium
3rd rowMediumSmall
4th rowLargeSmall
5th rowSmallMedium
ValueCountFrequency (%)
large 333964
33.4%
medium 333501
33.4%
small 332535
33.3%
ValueCountFrequency (%)
large 10123
33.7%
small 10028
33.4%
medium 9849
32.8%
2025-06-06T02:08:13.782034image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 667465
12.5%
a 666499
12.5%
m 666036
12.5%
l 665070
12.5%
g 333964
6.3%
r 333964
6.3%
L 333964
6.3%
M 333501
6.3%
i 333501
6.3%
d 333501
6.3%
Other values (2) 666036
12.5%
ValueCountFrequency (%)
a 20151
12.6%
l 20056
12.5%
e 19972
12.5%
m 19877
12.4%
g 10123
6.3%
r 10123
6.3%
L 10123
6.3%
S 10028
6.3%
M 9849
6.2%
d 9849
6.2%
Other values (2) 19698
12.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 5333501
100.0%
ValueCountFrequency (%)
(unknown) 159849
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 667465
12.5%
a 666499
12.5%
m 666036
12.5%
l 665070
12.5%
g 333964
6.3%
r 333964
6.3%
L 333964
6.3%
M 333501
6.3%
i 333501
6.3%
d 333501
6.3%
Other values (2) 666036
12.5%
ValueCountFrequency (%)
a 20151
12.6%
l 20056
12.5%
e 19972
12.5%
m 19877
12.4%
g 10123
6.3%
r 10123
6.3%
L 10123
6.3%
S 10028
6.3%
M 9849
6.2%
d 9849
6.2%
Other values (2) 19698
12.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 5333501
100.0%
ValueCountFrequency (%)
(unknown) 159849
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 667465
12.5%
a 666499
12.5%
m 666036
12.5%
l 665070
12.5%
g 333964
6.3%
r 333964
6.3%
L 333964
6.3%
M 333501
6.3%
i 333501
6.3%
d 333501
6.3%
Other values (2) 666036
12.5%
ValueCountFrequency (%)
a 20151
12.6%
l 20056
12.5%
e 19972
12.5%
m 19877
12.4%
g 10123
6.3%
r 10123
6.3%
L 10123
6.3%
S 10028
6.3%
M 9849
6.2%
d 9849
6.2%
Other values (2) 19698
12.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 5333501
100.0%
ValueCountFrequency (%)
(unknown) 159849
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 667465
12.5%
a 666499
12.5%
m 666036
12.5%
l 665070
12.5%
g 333964
6.3%
r 333964
6.3%
L 333964
6.3%
M 333501
6.3%
i 333501
6.3%
d 333501
6.3%
Other values (2) 666036
12.5%
ValueCountFrequency (%)
a 20151
12.6%
l 20056
12.5%
e 19972
12.5%
m 19877
12.4%
g 10123
6.3%
r 10123
6.3%
L 10123
6.3%
S 10028
6.3%
M 9849
6.2%
d 9849
6.2%
Other values (2) 19698
12.3%

product_weight
Real number (ℝ)

 Full DatasetSystematic Sample
Distinct991991
Distinct (%)0.1%3.3%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean5.054372385.061463
 Full DatasetSystematic Sample
Minimum0.10.1
Maximum1010
Zeros00
Zeros (%)0.0%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T02:08:14.017550image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Full DatasetSystematic Sample
Minimum0.10.1
5-th percentile0.60.62
Q12.582.58
median5.065.07
Q37.537.53
95-th percentile9.59.5
Maximum1010
Range9.99.9
Interquartile range (IQR)4.954.95

Descriptive statistics

 Full DatasetSystematic Sample
Standard deviation2.8578484872.855694378
Coefficient of variation (CV)0.565421040.5642033496
Kurtosis-1.200012392-1.196524814
Mean5.054372385.061463
Median Absolute Deviation (MAD)2.472.47
Skewness-0.001975515497-0.0007373572724
Sum5054372.38151843.89
Variance8.1672979778.154990383
MonotonicityNot monotonicNot monotonic
2025-06-06T02:08:14.355164image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2.51 1094
 
0.1%
7.79 1092
 
0.1%
3.96 1089
 
0.1%
3.55 1089
 
0.1%
1.61 1088
 
0.1%
5.24 1088
 
0.1%
1.74 1087
 
0.1%
4.66 1085
 
0.1%
3.04 1082
 
0.1%
1.22 1081
 
0.1%
Other values (981) 989125
98.9%
ValueCountFrequency (%)
8.14 49
 
0.2%
1.76 47
 
0.2%
5.85 46
 
0.2%
9.93 45
 
0.1%
2.2 45
 
0.1%
8.5 45
 
0.1%
5.21 45
 
0.1%
8.96 44
 
0.1%
1.45 44
 
0.1%
5.52 44
 
0.1%
Other values (981) 29546
98.5%
ValueCountFrequency (%)
0.1 506
0.1%
0.11 1031
0.1%
0.12 996
0.1%
0.13 1001
0.1%
0.14 1007
0.1%
ValueCountFrequency (%)
0.1 13
 
< 0.1%
0.11 19
0.1%
0.12 34
0.1%
0.13 27
0.1%
0.14 32
0.1%
ValueCountFrequency (%)
0.1 13
 
< 0.1%
0.11 19
< 0.1%
0.12 34
< 0.1%
0.13 27
< 0.1%
0.14 32
< 0.1%
ValueCountFrequency (%)
0.1 506
1.7%
0.11 1031
3.4%
0.12 996
3.3%
0.13 1001
3.3%
0.14 1007
3.4%

product_color
['Text', 'Text']

 Full DatasetSystematic Sample
Distinct55
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T02:08:14.755876image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

 Full DatasetSystematic Sample
Max length55
Median length55
Mean length4.3993974.4086
Min length33

Characters and Unicode

 Full DatasetSystematic Sample
Total characters4399397132258
Distinct characters1616
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Full DatasetSystematic Sample
Unique00 ?
Unique (%)0.0%0.0%

Sample

 Full DatasetSystematic Sample
1st rowRedRed
2nd rowBlueGreen
3rd rowGreenWhite
4th rowBlueWhite
5th rowRedWhite
ValueCountFrequency (%)
blue 200671
20.1%
green 200202
20.0%
red 199966
20.0%
black 199704
20.0%
white 199457
19.9%
ValueCountFrequency (%)
green 6117
20.4%
white 6051
20.2%
blue 5980
19.9%
black 5971
19.9%
red 5881
19.6%
2025-06-06T02:08:15.304445image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 1000498
22.7%
B 400375
 
9.1%
l 400375
 
9.1%
u 200671
 
4.6%
G 200202
 
4.6%
r 200202
 
4.6%
n 200202
 
4.6%
R 199966
 
4.5%
d 199966
 
4.5%
a 199704
 
4.5%
Other values (6) 1197236
27.2%
ValueCountFrequency (%)
e 30146
22.8%
B 11951
 
9.0%
l 11951
 
9.0%
G 6117
 
4.6%
r 6117
 
4.6%
n 6117
 
4.6%
W 6051
 
4.6%
h 6051
 
4.6%
t 6051
 
4.6%
i 6051
 
4.6%
Other values (6) 35655
27.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4399397
100.0%
ValueCountFrequency (%)
(unknown) 132258
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 1000498
22.7%
B 400375
 
9.1%
l 400375
 
9.1%
u 200671
 
4.6%
G 200202
 
4.6%
r 200202
 
4.6%
n 200202
 
4.6%
R 199966
 
4.5%
d 199966
 
4.5%
a 199704
 
4.5%
Other values (6) 1197236
27.2%
ValueCountFrequency (%)
e 30146
22.8%
B 11951
 
9.0%
l 11951
 
9.0%
G 6117
 
4.6%
r 6117
 
4.6%
n 6117
 
4.6%
W 6051
 
4.6%
h 6051
 
4.6%
t 6051
 
4.6%
i 6051
 
4.6%
Other values (6) 35655
27.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4399397
100.0%
ValueCountFrequency (%)
(unknown) 132258
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 1000498
22.7%
B 400375
 
9.1%
l 400375
 
9.1%
u 200671
 
4.6%
G 200202
 
4.6%
r 200202
 
4.6%
n 200202
 
4.6%
R 199966
 
4.5%
d 199966
 
4.5%
a 199704
 
4.5%
Other values (6) 1197236
27.2%
ValueCountFrequency (%)
e 30146
22.8%
B 11951
 
9.0%
l 11951
 
9.0%
G 6117
 
4.6%
r 6117
 
4.6%
n 6117
 
4.6%
W 6051
 
4.6%
h 6051
 
4.6%
t 6051
 
4.6%
i 6051
 
4.6%
Other values (6) 35655
27.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4399397
100.0%
ValueCountFrequency (%)
(unknown) 132258
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 1000498
22.7%
B 400375
 
9.1%
l 400375
 
9.1%
u 200671
 
4.6%
G 200202
 
4.6%
r 200202
 
4.6%
n 200202
 
4.6%
R 199966
 
4.5%
d 199966
 
4.5%
a 199704
 
4.5%
Other values (6) 1197236
27.2%
ValueCountFrequency (%)
e 30146
22.8%
B 11951
 
9.0%
l 11951
 
9.0%
G 6117
 
4.6%
r 6117
 
4.6%
n 6117
 
4.6%
W 6051
 
4.6%
h 6051
 
4.6%
t 6051
 
4.6%
i 6051
 
4.6%
Other values (6) 35655
27.0%

product_material
['Text', 'Text']

 Full DatasetSystematic Sample
Distinct44
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T02:08:15.670377image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

 Full DatasetSystematic Sample
Max length77
Median length55
Mean length5.250875.254966667
Min length44

Characters and Unicode

 Full DatasetSystematic Sample
Total characters5250870157649
Distinct characters1313
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Full DatasetSystematic Sample
Unique00 ?
Unique (%)0.0%0.0%

Sample

 Full DatasetSystematic Sample
1st rowMetalMetal
2nd rowMetalPlastic
3rd rowPlasticMetal
4th rowWoodMetal
5th rowMetalMetal
ValueCountFrequency (%)
plastic 250483
25.0%
wood 250096
25.0%
metal 249896
25.0%
glass 249525
25.0%
ValueCountFrequency (%)
glass 7732
25.8%
plastic 7488
25.0%
metal 7453
24.8%
wood 7327
24.4%
2025-06-06T02:08:16.041875image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
l 749904
14.3%
a 749904
14.3%
s 749533
14.3%
t 500379
9.5%
o 500192
9.5%
P 250483
 
4.8%
i 250483
 
4.8%
c 250483
 
4.8%
W 250096
 
4.8%
d 250096
 
4.8%
Other values (3) 749317
14.3%
ValueCountFrequency (%)
s 22952
14.6%
a 22673
14.4%
l 22673
14.4%
t 14941
9.5%
o 14654
9.3%
G 7732
 
4.9%
P 7488
 
4.7%
c 7488
 
4.7%
i 7488
 
4.7%
M 7453
 
4.7%
Other values (3) 22107
14.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 5250870
100.0%
ValueCountFrequency (%)
(unknown) 157649
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
l 749904
14.3%
a 749904
14.3%
s 749533
14.3%
t 500379
9.5%
o 500192
9.5%
P 250483
 
4.8%
i 250483
 
4.8%
c 250483
 
4.8%
W 250096
 
4.8%
d 250096
 
4.8%
Other values (3) 749317
14.3%
ValueCountFrequency (%)
s 22952
14.6%
a 22673
14.4%
l 22673
14.4%
t 14941
9.5%
o 14654
9.3%
G 7732
 
4.9%
P 7488
 
4.7%
c 7488
 
4.7%
i 7488
 
4.7%
M 7453
 
4.7%
Other values (3) 22107
14.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 5250870
100.0%
ValueCountFrequency (%)
(unknown) 157649
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
l 749904
14.3%
a 749904
14.3%
s 749533
14.3%
t 500379
9.5%
o 500192
9.5%
P 250483
 
4.8%
i 250483
 
4.8%
c 250483
 
4.8%
W 250096
 
4.8%
d 250096
 
4.8%
Other values (3) 749317
14.3%
ValueCountFrequency (%)
s 22952
14.6%
a 22673
14.4%
l 22673
14.4%
t 14941
9.5%
o 14654
9.3%
G 7732
 
4.9%
P 7488
 
4.7%
c 7488
 
4.7%
i 7488
 
4.7%
M 7453
 
4.7%
Other values (3) 22107
14.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 5250870
100.0%
ValueCountFrequency (%)
(unknown) 157649
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
l 749904
14.3%
a 749904
14.3%
s 749533
14.3%
t 500379
9.5%
o 500192
9.5%
P 250483
 
4.8%
i 250483
 
4.8%
c 250483
 
4.8%
W 250096
 
4.8%
d 250096
 
4.8%
Other values (3) 749317
14.3%
ValueCountFrequency (%)
s 22952
14.6%
a 22673
14.4%
l 22673
14.4%
t 14941
9.5%
o 14654
9.3%
G 7732
 
4.9%
P 7488
 
4.7%
c 7488
 
4.7%
i 7488
 
4.7%
M 7453
 
4.7%
Other values (3) 22107
14.0%

product_manufacture_date
['Text', 'Text']

 Full DatasetSystematic Sample
Distinct99203729991
Distinct (%)99.2%> 99.9%
Missing00
Missing (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T02:08:16.721156image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

 Full DatasetSystematic Sample
Max length1919
Median length1919
Mean length1919
Min length1919

Characters and Unicode

 Full DatasetSystematic Sample
Total characters19000000570000
Distinct characters1313
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Full DatasetSystematic Sample
Unique98412629982 ?
Unique (%)98.4%99.9%

Sample

 Full DatasetSystematic Sample
1st row2019-08-04 01:47:012019-08-04 01:47:01
2nd row2019-10-23 19:59:172019-09-19 10:14:11
3rd row2018-05-12 08:00:292019-02-04 10:47:41
4th row2019-11-15 16:17:292019-01-04 09:40:43
5th row2019-08-27 02:58:192019-05-27 11:21:51
ValueCountFrequency (%)
2018-04-10 1514
 
0.1%
2019-03-19 1490
 
0.1%
2018-02-26 1471
 
0.1%
2018-06-18 1467
 
0.1%
2018-09-24 1462
 
0.1%
2019-01-25 1457
 
0.1%
2019-01-30 1456
 
0.1%
2018-04-28 1454
 
0.1%
2019-07-04 1453
 
0.1%
2019-01-09 1453
 
0.1%
Other values (87119) 1985323
99.3%
ValueCountFrequency (%)
2019-10-10 66
 
0.1%
2018-05-25 60
 
0.1%
2018-03-20 57
 
0.1%
2018-02-25 57
 
0.1%
2018-08-27 57
 
0.1%
2018-01-23 56
 
0.1%
2018-01-06 55
 
0.1%
2019-11-21 55
 
0.1%
2018-06-16 55
 
0.1%
2019-05-12 55
 
0.1%
Other values (26164) 59427
99.0%
2025-06-06T02:08:17.531544image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3297851
17.4%
1 2942646
15.5%
2 2411227
12.7%
- 2000000
10.5%
: 2000000
10.5%
1000000
 
5.3%
8 967248
 
5.1%
9 961589
 
5.1%
3 891404
 
4.7%
5 799916
 
4.2%
Other values (3) 1728119
9.1%
ValueCountFrequency (%)
0 98980
17.4%
1 88196
15.5%
2 72387
12.7%
- 60000
10.5%
: 60000
10.5%
30000
 
5.3%
9 28977
 
5.1%
8 28940
 
5.1%
3 26720
 
4.7%
5 24008
 
4.2%
Other values (3) 51792
9.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 19000000
100.0%
ValueCountFrequency (%)
(unknown) 570000
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 3297851
17.4%
1 2942646
15.5%
2 2411227
12.7%
- 2000000
10.5%
: 2000000
10.5%
1000000
 
5.3%
8 967248
 
5.1%
9 961589
 
5.1%
3 891404
 
4.7%
5 799916
 
4.2%
Other values (3) 1728119
9.1%
ValueCountFrequency (%)
0 98980
17.4%
1 88196
15.5%
2 72387
12.7%
- 60000
10.5%
: 60000
10.5%
30000
 
5.3%
9 28977
 
5.1%
8 28940
 
5.1%
3 26720
 
4.7%
5 24008
 
4.2%
Other values (3) 51792
9.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 19000000
100.0%
ValueCountFrequency (%)
(unknown) 570000
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 3297851
17.4%
1 2942646
15.5%
2 2411227
12.7%
- 2000000
10.5%
: 2000000
10.5%
1000000
 
5.3%
8 967248
 
5.1%
9 961589
 
5.1%
3 891404
 
4.7%
5 799916
 
4.2%
Other values (3) 1728119
9.1%
ValueCountFrequency (%)
0 98980
17.4%
1 88196
15.5%
2 72387
12.7%
- 60000
10.5%
: 60000
10.5%
30000
 
5.3%
9 28977
 
5.1%
8 28940
 
5.1%
3 26720
 
4.7%
5 24008
 
4.2%
Other values (3) 51792
9.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 19000000
100.0%
ValueCountFrequency (%)
(unknown) 570000
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 3297851
17.4%
1 2942646
15.5%
2 2411227
12.7%
- 2000000
10.5%
: 2000000
10.5%
1000000
 
5.3%
8 967248
 
5.1%
9 961589
 
5.1%
3 891404
 
4.7%
5 799916
 
4.2%
Other values (3) 1728119
9.1%
ValueCountFrequency (%)
0 98980
17.4%
1 88196
15.5%
2 72387
12.7%
- 60000
10.5%
: 60000
10.5%
30000
 
5.3%
9 28977
 
5.1%
8 28940
 
5.1%
3 26720
 
4.7%
5 24008
 
4.2%
Other values (3) 51792
9.1%

product_expiry_date
['Text', 'Text']

 Full DatasetSystematic Sample
Distinct99204229994
Distinct (%)99.2%> 99.9%
Missing00
Missing (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T02:08:18.254919image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

 Full DatasetSystematic Sample
Max length1919
Median length1919
Mean length1919
Min length1919

Characters and Unicode

 Full DatasetSystematic Sample
Total characters19000000570000
Distinct characters1313
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Full DatasetSystematic Sample
Unique98412129988 ?
Unique (%)98.4%> 99.9%

Sample

 Full DatasetSystematic Sample
1st row2022-05-28 14:54:022022-05-28 14:54:02
2nd row2022-12-19 08:04:412022-12-02 10:27:26
3rd row2023-02-01 12:15:072022-11-25 00:36:25
4th row2023-02-05 11:46:572023-04-21 18:13:36
5th row2023-10-05 08:13:072023-03-09 01:20:13
ValueCountFrequency (%)
2022-12-22 1476
 
0.1%
2022-06-08 1475
 
0.1%
2022-01-28 1473
 
0.1%
2023-03-13 1472
 
0.1%
2022-10-06 1468
 
0.1%
2022-06-27 1468
 
0.1%
2023-07-08 1457
 
0.1%
2023-07-23 1457
 
0.1%
2023-01-11 1452
 
0.1%
2022-04-17 1450
 
0.1%
Other values (87119) 1985352
99.3%
ValueCountFrequency (%)
2022-09-23 63
 
0.1%
2023-09-19 60
 
0.1%
2022-07-26 59
 
0.1%
2022-02-19 59
 
0.1%
2022-11-29 57
 
0.1%
2023-10-05 56
 
0.1%
2023-12-10 56
 
0.1%
2022-12-18 56
 
0.1%
2022-08-25 55
 
0.1%
2022-07-19 55
 
0.1%
Other values (26049) 59424
99.0%
2025-06-06T02:08:19.053893image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 3911569
20.6%
0 3298912
17.4%
- 2000000
10.5%
: 2000000
10.5%
1 1939371
10.2%
3 1392537
 
7.3%
1000000
 
5.3%
5 800253
 
4.2%
4 798405
 
4.2%
8 467536
 
2.5%
Other values (3) 1391417
 
7.3%
ValueCountFrequency (%)
2 117442
20.6%
0 99034
17.4%
- 60000
10.5%
: 60000
10.5%
1 58229
10.2%
3 41580
 
7.3%
30000
 
5.3%
5 24249
 
4.3%
4 23712
 
4.2%
7 14077
 
2.5%
Other values (3) 41677
 
7.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 19000000
100.0%
ValueCountFrequency (%)
(unknown) 570000
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
2 3911569
20.6%
0 3298912
17.4%
- 2000000
10.5%
: 2000000
10.5%
1 1939371
10.2%
3 1392537
 
7.3%
1000000
 
5.3%
5 800253
 
4.2%
4 798405
 
4.2%
8 467536
 
2.5%
Other values (3) 1391417
 
7.3%
ValueCountFrequency (%)
2 117442
20.6%
0 99034
17.4%
- 60000
10.5%
: 60000
10.5%
1 58229
10.2%
3 41580
 
7.3%
30000
 
5.3%
5 24249
 
4.3%
4 23712
 
4.2%
7 14077
 
2.5%
Other values (3) 41677
 
7.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 19000000
100.0%
ValueCountFrequency (%)
(unknown) 570000
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
2 3911569
20.6%
0 3298912
17.4%
- 2000000
10.5%
: 2000000
10.5%
1 1939371
10.2%
3 1392537
 
7.3%
1000000
 
5.3%
5 800253
 
4.2%
4 798405
 
4.2%
8 467536
 
2.5%
Other values (3) 1391417
 
7.3%
ValueCountFrequency (%)
2 117442
20.6%
0 99034
17.4%
- 60000
10.5%
: 60000
10.5%
1 58229
10.2%
3 41580
 
7.3%
30000
 
5.3%
5 24249
 
4.3%
4 23712
 
4.2%
7 14077
 
2.5%
Other values (3) 41677
 
7.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 19000000
100.0%
ValueCountFrequency (%)
(unknown) 570000
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
2 3911569
20.6%
0 3298912
17.4%
- 2000000
10.5%
: 2000000
10.5%
1 1939371
10.2%
3 1392537
 
7.3%
1000000
 
5.3%
5 800253
 
4.2%
4 798405
 
4.2%
8 467536
 
2.5%
Other values (3) 1391417
 
7.3%
ValueCountFrequency (%)
2 117442
20.6%
0 99034
17.4%
- 60000
10.5%
: 60000
10.5%
1 58229
10.2%
3 41580
 
7.3%
30000
 
5.3%
5 24249
 
4.3%
4 23712
 
4.2%
7 14077
 
2.5%
Other values (3) 41677
 
7.3%

product_shelf_life
Real number (ℝ)

 Full DatasetSystematic Sample
Distinct365365
Distinct (%)< 0.1%1.2%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean181.876207181.6946667
 Full DatasetSystematic Sample
Minimum00
Maximum364364
Zeros271363
Zeros (%)0.3%0.2%
Negative00
Negative (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T02:08:19.232339image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Full DatasetSystematic Sample
Minimum00
5-th percentile1818
Q19192
median182181
Q3273272
95-th percentile346346
Maximum364364
Range364364
Interquartile range (IQR)182180

Descriptive statistics

 Full DatasetSystematic Sample
Standard deviation105.2288552104.9073453
Coefficient of variation (CV)0.57857405850.5773826342
Kurtosis-1.198082782-1.187975675
Mean181.876207181.6946667
Median Absolute Deviation (MAD)9190
Skewness0.00062292044490.002701780176
Sum1818762075450840
Variance11073.1119711005.55109
MonotonicityNot monotonicNot monotonic
2025-06-06T02:08:19.464933image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
87 2893
 
0.3%
272 2874
 
0.3%
70 2870
 
0.3%
250 2870
 
0.3%
210 2862
 
0.3%
224 2859
 
0.3%
238 2857
 
0.3%
33 2848
 
0.3%
297 2847
 
0.3%
171 2845
 
0.3%
Other values (355) 971375
97.1%
ValueCountFrequency (%)
125 111
 
0.4%
5 110
 
0.4%
248 109
 
0.4%
273 107
 
0.4%
322 107
 
0.4%
285 106
 
0.4%
82 102
 
0.3%
93 102
 
0.3%
306 101
 
0.3%
291 101
 
0.3%
Other values (355) 28944
96.5%
ValueCountFrequency (%)
0 2713
0.3%
1 2788
0.3%
2 2776
0.3%
3 2725
0.3%
4 2788
0.3%
ValueCountFrequency (%)
0 63
0.2%
1 76
0.3%
2 77
0.3%
3 94
0.3%
4 78
0.3%
ValueCountFrequency (%)
0 63
< 0.1%
1 76
< 0.1%
2 77
< 0.1%
3 94
< 0.1%
4 78
< 0.1%
ValueCountFrequency (%)
0 2713
9.0%
1 2788
9.3%
2 2776
9.3%
3 2725
9.1%
4 2788
9.3%

promotion_id
Real number (ℝ)

 Full DatasetSystematic Sample
Distinct999999
Distinct (%)0.1%3.3%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean499.920037498.2946667
 Full DatasetSystematic Sample
Minimum11
Maximum999999
Zeros00
Zeros (%)0.0%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T02:08:19.680908image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Full DatasetSystematic Sample
Minimum11
5-th percentile5051.95
Q1250249
median500499
Q3750746
95-th percentile949949
Maximum999999
Range998998
Interquartile range (IQR)500497

Descriptive statistics

 Full DatasetSystematic Sample
Standard deviation288.4530565288.2730145
Coefficient of variation (CV)0.576998390.578519165
Kurtosis-1.200677574-1.203212649
Mean499.920037498.2946667
Median Absolute Deviation (MAD)250248
Skewness-0.00089350443320.008814299235
Sum49992003714948840
Variance83205.1657983101.33088
MonotonicityNot monotonicNot monotonic
2025-06-06T02:08:19.891834image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
52 1092
 
0.1%
94 1082
 
0.1%
374 1079
 
0.1%
117 1077
 
0.1%
29 1075
 
0.1%
603 1075
 
0.1%
512 1073
 
0.1%
949 1073
 
0.1%
885 1073
 
0.1%
51 1070
 
0.1%
Other values (989) 989231
98.9%
ValueCountFrequency (%)
462 49
 
0.2%
396 48
 
0.2%
793 48
 
0.2%
666 47
 
0.2%
311 46
 
0.2%
306 46
 
0.2%
740 45
 
0.1%
670 45
 
0.1%
361 45
 
0.1%
282 44
 
0.1%
Other values (989) 29537
98.5%
ValueCountFrequency (%)
1 1033
0.1%
2 995
0.1%
3 1036
0.1%
4 1024
0.1%
5 992
0.1%
ValueCountFrequency (%)
1 40
0.1%
2 31
0.1%
3 30
0.1%
4 42
0.1%
5 37
0.1%
ValueCountFrequency (%)
1 40
< 0.1%
2 31
< 0.1%
3 30
< 0.1%
4 42
< 0.1%
5 37
< 0.1%
ValueCountFrequency (%)
1 1033
3.4%
2 995
3.3%
3 1036
3.5%
4 1024
3.4%
5 992
3.3%

promotion_type
['Text', 'Text']

 Full DatasetSystematic Sample
Distinct33
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T02:08:20.187107image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

 Full DatasetSystematic Sample
Max length2020
Median length1010
Mean length12.33406412.36263333
Min length77

Characters and Unicode

 Full DatasetSystematic Sample
Total characters12334064370879
Distinct characters2020
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Full DatasetSystematic Sample
Unique00 ?
Unique (%)0.0%0.0%

Sample

 Full DatasetSystematic Sample
1st row20% Off20% Off
2nd rowFlash SaleFlash Sale
3rd rowFlash SaleFlash Sale
4th rowBuy One Get One FreeBuy One Get One Free
5th rowFlash SaleFlash Sale
ValueCountFrequency (%)
one 667040
22.2%
20 333712
11.1%
off 333712
11.1%
buy 333520
11.1%
get 333520
11.1%
free 333520
11.1%
flash 332768
11.1%
sale 332768
11.1%
ValueCountFrequency (%)
one 20174
22.4%
buy 10087
11.2%
get 10087
11.2%
free 10087
11.2%
20 9997
11.1%
off 9997
11.1%
flash 9916
11.0%
sale 9916
11.0%
2025-06-06T02:08:20.513531image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2000560
16.2%
e 2000368
16.2%
O 1000752
 
8.1%
f 667424
 
5.4%
n 667040
 
5.4%
F 666288
 
5.4%
a 665536
 
5.4%
l 665536
 
5.4%
% 333712
 
2.7%
0 333712
 
2.7%
Other values (10) 3333136
27.0%
ValueCountFrequency (%)
e 60351
16.3%
60261
16.2%
O 30171
 
8.1%
n 20174
 
5.4%
F 20003
 
5.4%
f 19994
 
5.4%
a 19832
 
5.3%
l 19832
 
5.3%
y 10087
 
2.7%
u 10087
 
2.7%
Other values (10) 100087
27.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 12334064
100.0%
ValueCountFrequency (%)
(unknown) 370879
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
2000560
16.2%
e 2000368
16.2%
O 1000752
 
8.1%
f 667424
 
5.4%
n 667040
 
5.4%
F 666288
 
5.4%
a 665536
 
5.4%
l 665536
 
5.4%
% 333712
 
2.7%
0 333712
 
2.7%
Other values (10) 3333136
27.0%
ValueCountFrequency (%)
e 60351
16.3%
60261
16.2%
O 30171
 
8.1%
n 20174
 
5.4%
F 20003
 
5.4%
f 19994
 
5.4%
a 19832
 
5.3%
l 19832
 
5.3%
y 10087
 
2.7%
u 10087
 
2.7%
Other values (10) 100087
27.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 12334064
100.0%
ValueCountFrequency (%)
(unknown) 370879
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
2000560
16.2%
e 2000368
16.2%
O 1000752
 
8.1%
f 667424
 
5.4%
n 667040
 
5.4%
F 666288
 
5.4%
a 665536
 
5.4%
l 665536
 
5.4%
% 333712
 
2.7%
0 333712
 
2.7%
Other values (10) 3333136
27.0%
ValueCountFrequency (%)
e 60351
16.3%
60261
16.2%
O 30171
 
8.1%
n 20174
 
5.4%
F 20003
 
5.4%
f 19994
 
5.4%
a 19832
 
5.3%
l 19832
 
5.3%
y 10087
 
2.7%
u 10087
 
2.7%
Other values (10) 100087
27.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 12334064
100.0%
ValueCountFrequency (%)
(unknown) 370879
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
2000560
16.2%
e 2000368
16.2%
O 1000752
 
8.1%
f 667424
 
5.4%
n 667040
 
5.4%
F 666288
 
5.4%
a 665536
 
5.4%
l 665536
 
5.4%
% 333712
 
2.7%
0 333712
 
2.7%
Other values (10) 3333136
27.0%
ValueCountFrequency (%)
e 60351
16.3%
60261
16.2%
O 30171
 
8.1%
n 20174
 
5.4%
F 20003
 
5.4%
f 19994
 
5.4%
a 19832
 
5.3%
l 19832
 
5.3%
y 10087
 
2.7%
u 10087
 
2.7%
Other values (10) 100087
27.0%

promotion_start_date
['Text', 'Text']

 Full DatasetSystematic Sample
Distinct98425829984
Distinct (%)98.4%99.9%
Missing00
Missing (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T02:08:21.250136image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

 Full DatasetSystematic Sample
Max length1919
Median length1919
Mean length1919
Min length1919

Characters and Unicode

 Full DatasetSystematic Sample
Total characters19000000570000
Distinct characters1313
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Full DatasetSystematic Sample
Unique96868129968 ?
Unique (%)96.9%99.9%

Sample

 Full DatasetSystematic Sample
1st row2021-07-14 14:28:422021-07-14 14:28:42
2nd row2021-09-23 04:26:092021-06-04 11:16:45
3rd row2021-06-13 12:31:152021-12-31 18:17:24
4th row2021-05-23 05:42:482021-02-14 04:10:44
5th row2021-04-19 04:55:322021-09-23 11:20:57
ValueCountFrequency (%)
2021-03-05 2885
 
0.1%
2021-02-07 2874
 
0.1%
2021-06-23 2871
 
0.1%
2021-05-15 2867
 
0.1%
2021-08-27 2863
 
0.1%
2021-11-04 2862
 
0.1%
2021-03-25 2858
 
0.1%
2021-09-06 2854
 
0.1%
2021-12-21 2851
 
0.1%
2021-08-06 2850
 
0.1%
Other values (86754) 1971365
98.6%
ValueCountFrequency (%)
2021-09-08 116
 
0.2%
2021-06-29 108
 
0.2%
2021-09-21 108
 
0.2%
2021-07-28 106
 
0.2%
2021-04-21 106
 
0.2%
2021-09-20 105
 
0.2%
2021-03-04 103
 
0.2%
2021-09-23 102
 
0.2%
2021-03-14 101
 
0.2%
2021-11-14 101
 
0.2%
Other values (25798) 58944
98.2%
2025-06-06T02:08:22.687996image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 3411867
18.0%
0 3300257
17.4%
1 2938965
15.5%
- 2000000
10.5%
: 2000000
10.5%
1000000
 
5.3%
3 890896
 
4.7%
5 800172
 
4.2%
4 796605
 
4.2%
7 468643
 
2.5%
Other values (3) 1392595
7.3%
ValueCountFrequency (%)
2 102036
17.9%
0 99116
17.4%
1 88203
15.5%
- 60000
10.5%
: 60000
10.5%
30000
 
5.3%
3 26783
 
4.7%
4 24136
 
4.2%
5 23982
 
4.2%
8 13996
 
2.5%
Other values (3) 41748
7.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 19000000
100.0%
ValueCountFrequency (%)
(unknown) 570000
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
2 3411867
18.0%
0 3300257
17.4%
1 2938965
15.5%
- 2000000
10.5%
: 2000000
10.5%
1000000
 
5.3%
3 890896
 
4.7%
5 800172
 
4.2%
4 796605
 
4.2%
7 468643
 
2.5%
Other values (3) 1392595
7.3%
ValueCountFrequency (%)
2 102036
17.9%
0 99116
17.4%
1 88203
15.5%
- 60000
10.5%
: 60000
10.5%
30000
 
5.3%
3 26783
 
4.7%
4 24136
 
4.2%
5 23982
 
4.2%
8 13996
 
2.5%
Other values (3) 41748
7.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 19000000
100.0%
ValueCountFrequency (%)
(unknown) 570000
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
2 3411867
18.0%
0 3300257
17.4%
1 2938965
15.5%
- 2000000
10.5%
: 2000000
10.5%
1000000
 
5.3%
3 890896
 
4.7%
5 800172
 
4.2%
4 796605
 
4.2%
7 468643
 
2.5%
Other values (3) 1392595
7.3%
ValueCountFrequency (%)
2 102036
17.9%
0 99116
17.4%
1 88203
15.5%
- 60000
10.5%
: 60000
10.5%
30000
 
5.3%
3 26783
 
4.7%
4 24136
 
4.2%
5 23982
 
4.2%
8 13996
 
2.5%
Other values (3) 41748
7.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 19000000
100.0%
ValueCountFrequency (%)
(unknown) 570000
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
2 3411867
18.0%
0 3300257
17.4%
1 2938965
15.5%
- 2000000
10.5%
: 2000000
10.5%
1000000
 
5.3%
3 890896
 
4.7%
5 800172
 
4.2%
4 796605
 
4.2%
7 468643
 
2.5%
Other values (3) 1392595
7.3%
ValueCountFrequency (%)
2 102036
17.9%
0 99116
17.4%
1 88203
15.5%
- 60000
10.5%
: 60000
10.5%
30000
 
5.3%
3 26783
 
4.7%
4 24136
 
4.2%
5 23982
 
4.2%
8 13996
 
2.5%
Other values (3) 41748
7.3%

promotion_end_date
['Text', 'Text']

 Full DatasetSystematic Sample
Distinct98425229987
Distinct (%)98.4%> 99.9%
Missing00
Missing (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T02:08:23.373000image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

 Full DatasetSystematic Sample
Max length1919
Median length1919
Mean length1919
Min length1919

Characters and Unicode

 Full DatasetSystematic Sample
Total characters19000000570000
Distinct characters1313
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Full DatasetSystematic Sample
Unique96867629974 ?
Unique (%)96.9%99.9%

Sample

 Full DatasetSystematic Sample
1st row2022-12-30 13:04:132022-12-30 13:04:13
2nd row2022-09-13 03:16:262022-10-18 02:50:42
3rd row2022-03-13 00:53:352022-06-01 09:36:45
4th row2022-02-06 00:42:302022-10-04 11:53:46
5th row2022-12-04 13:07:092022-11-26 17:32:39
ValueCountFrequency (%)
2022-08-06 2905
 
0.1%
2022-03-08 2896
 
0.1%
2022-09-28 2874
 
0.1%
2022-02-22 2873
 
0.1%
2022-09-16 2872
 
0.1%
2022-06-10 2865
 
0.1%
2022-07-13 2858
 
0.1%
2022-12-15 2854
 
0.1%
2022-12-31 2847
 
0.1%
2022-08-25 2842
 
0.1%
Other values (86755) 1971314
98.6%
ValueCountFrequency (%)
2022-06-16 112
 
0.2%
2022-08-30 106
 
0.2%
2022-02-19 105
 
0.2%
2022-11-28 104
 
0.2%
2022-08-26 103
 
0.2%
2022-01-30 102
 
0.2%
2022-04-08 102
 
0.2%
2022-06-04 102
 
0.2%
2022-12-01 101
 
0.2%
2022-01-15 101
 
0.2%
Other values (25716) 58962
98.3%
2025-06-06T02:08:24.394841image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 4411397
23.2%
0 3299242
17.4%
- 2000000
10.5%
: 2000000
10.5%
1 1940750
10.2%
1000000
 
5.3%
3 890892
 
4.7%
5 800852
 
4.2%
4 797493
 
4.2%
8 467852
 
2.5%
Other values (3) 1391522
 
7.3%
ValueCountFrequency (%)
2 132318
23.2%
0 98859
17.3%
- 60000
10.5%
: 60000
10.5%
1 58509
10.3%
30000
 
5.3%
3 26731
 
4.7%
5 24132
 
4.2%
4 23830
 
4.2%
8 14042
 
2.5%
Other values (3) 41579
 
7.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 19000000
100.0%
ValueCountFrequency (%)
(unknown) 570000
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
2 4411397
23.2%
0 3299242
17.4%
- 2000000
10.5%
: 2000000
10.5%
1 1940750
10.2%
1000000
 
5.3%
3 890892
 
4.7%
5 800852
 
4.2%
4 797493
 
4.2%
8 467852
 
2.5%
Other values (3) 1391522
 
7.3%
ValueCountFrequency (%)
2 132318
23.2%
0 98859
17.3%
- 60000
10.5%
: 60000
10.5%
1 58509
10.3%
30000
 
5.3%
3 26731
 
4.7%
5 24132
 
4.2%
4 23830
 
4.2%
8 14042
 
2.5%
Other values (3) 41579
 
7.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 19000000
100.0%
ValueCountFrequency (%)
(unknown) 570000
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
2 4411397
23.2%
0 3299242
17.4%
- 2000000
10.5%
: 2000000
10.5%
1 1940750
10.2%
1000000
 
5.3%
3 890892
 
4.7%
5 800852
 
4.2%
4 797493
 
4.2%
8 467852
 
2.5%
Other values (3) 1391522
 
7.3%
ValueCountFrequency (%)
2 132318
23.2%
0 98859
17.3%
- 60000
10.5%
: 60000
10.5%
1 58509
10.3%
30000
 
5.3%
3 26731
 
4.7%
5 24132
 
4.2%
4 23830
 
4.2%
8 14042
 
2.5%
Other values (3) 41579
 
7.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 19000000
100.0%
ValueCountFrequency (%)
(unknown) 570000
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
2 4411397
23.2%
0 3299242
17.4%
- 2000000
10.5%
: 2000000
10.5%
1 1940750
10.2%
1000000
 
5.3%
3 890892
 
4.7%
5 800852
 
4.2%
4 797493
 
4.2%
8 467852
 
2.5%
Other values (3) 1391522
 
7.3%
ValueCountFrequency (%)
2 132318
23.2%
0 98859
17.3%
- 60000
10.5%
: 60000
10.5%
1 58509
10.3%
30000
 
5.3%
3 26731
 
4.7%
5 24132
 
4.2%
4 23830
 
4.2%
8 14042
 
2.5%
Other values (3) 41579
 
7.3%

promotion_effectiveness
['Text', 'Text']

 Full DatasetSystematic Sample
Distinct33
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T02:08:24.706018image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

 Full DatasetSystematic Sample
Max length66
Median length44
Mean length4.3334074.339933333
Min length33

Characters and Unicode

 Full DatasetSystematic Sample
Total characters4333407130198
Distinct characters1212
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Full DatasetSystematic Sample
Unique00 ?
Unique (%)0.0%0.0%

Sample

 Full DatasetSystematic Sample
1st rowHighHigh
2nd rowLowMedium
3rd rowLowHigh
4th rowHighHigh
5th rowMediumHigh
ValueCountFrequency (%)
high 333660
33.4%
medium 333249
33.3%
low 333091
33.3%
ValueCountFrequency (%)
medium 10112
33.7%
low 10026
33.4%
high 9862
32.9%
2025-06-06T02:08:25.178856image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i 666909
15.4%
H 333660
7.7%
g 333660
7.7%
h 333660
7.7%
M 333249
7.7%
e 333249
7.7%
d 333249
7.7%
u 333249
7.7%
m 333249
7.7%
L 333091
7.7%
Other values (2) 666182
15.4%
ValueCountFrequency (%)
i 19974
15.3%
M 10112
7.8%
e 10112
7.8%
d 10112
7.8%
u 10112
7.8%
m 10112
7.8%
L 10026
7.7%
o 10026
7.7%
w 10026
7.7%
H 9862
7.6%
Other values (2) 19724
15.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4333407
100.0%
ValueCountFrequency (%)
(unknown) 130198
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
i 666909
15.4%
H 333660
7.7%
g 333660
7.7%
h 333660
7.7%
M 333249
7.7%
e 333249
7.7%
d 333249
7.7%
u 333249
7.7%
m 333249
7.7%
L 333091
7.7%
Other values (2) 666182
15.4%
ValueCountFrequency (%)
i 19974
15.3%
M 10112
7.8%
e 10112
7.8%
d 10112
7.8%
u 10112
7.8%
m 10112
7.8%
L 10026
7.7%
o 10026
7.7%
w 10026
7.7%
H 9862
7.6%
Other values (2) 19724
15.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4333407
100.0%
ValueCountFrequency (%)
(unknown) 130198
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
i 666909
15.4%
H 333660
7.7%
g 333660
7.7%
h 333660
7.7%
M 333249
7.7%
e 333249
7.7%
d 333249
7.7%
u 333249
7.7%
m 333249
7.7%
L 333091
7.7%
Other values (2) 666182
15.4%
ValueCountFrequency (%)
i 19974
15.3%
M 10112
7.8%
e 10112
7.8%
d 10112
7.8%
u 10112
7.8%
m 10112
7.8%
L 10026
7.7%
o 10026
7.7%
w 10026
7.7%
H 9862
7.6%
Other values (2) 19724
15.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4333407
100.0%
ValueCountFrequency (%)
(unknown) 130198
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
i 666909
15.4%
H 333660
7.7%
g 333660
7.7%
h 333660
7.7%
M 333249
7.7%
e 333249
7.7%
d 333249
7.7%
u 333249
7.7%
m 333249
7.7%
L 333091
7.7%
Other values (2) 666182
15.4%
ValueCountFrequency (%)
i 19974
15.3%
M 10112
7.8%
e 10112
7.8%
d 10112
7.8%
u 10112
7.8%
m 10112
7.8%
L 10026
7.7%
o 10026
7.7%
w 10026
7.7%
H 9862
7.6%
Other values (2) 19724
15.1%

promotion_channel
['Text', 'Text']

 Full DatasetSystematic Sample
Distinct33
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T02:08:25.519917image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

 Full DatasetSystematic Sample
Max length1212
Median length88
Mean length8.6654288.6592
Min length66

Characters and Unicode

 Full DatasetSystematic Sample
Total characters8665428259776
Distinct characters1717
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Full DatasetSystematic Sample
Unique00 ?
Unique (%)0.0%0.0%

Sample

 Full DatasetSystematic Sample
1st rowOnlineOnline
2nd rowSocial MediaIn-store
3rd rowOnlineIn-store
4th rowSocial MediaSocial Media
5th rowOnlineSocial Media
ValueCountFrequency (%)
online 333694
25.0%
social 333204
25.0%
media 333204
25.0%
in-store 333102
25.0%
ValueCountFrequency (%)
online 10026
25.1%
in-store 10017
25.1%
social 9957
24.9%
media 9957
24.9%
2025-06-06T02:08:26.079330image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n 1000490
11.5%
i 1000102
11.5%
e 1000000
11.5%
l 666898
 
7.7%
a 666408
 
7.7%
o 666306
 
7.7%
O 333694
 
3.9%
S 333204
 
3.8%
c 333204
 
3.8%
333204
 
3.8%
Other values (7) 2331918
26.9%
ValueCountFrequency (%)
n 30069
11.6%
e 30000
11.5%
i 29940
11.5%
l 19983
 
7.7%
o 19974
 
7.7%
a 19914
 
7.7%
O 10026
 
3.9%
I 10017
 
3.9%
- 10017
 
3.9%
t 10017
 
3.9%
Other values (7) 69819
26.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 8665428
100.0%
ValueCountFrequency (%)
(unknown) 259776
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
n 1000490
11.5%
i 1000102
11.5%
e 1000000
11.5%
l 666898
 
7.7%
a 666408
 
7.7%
o 666306
 
7.7%
O 333694
 
3.9%
S 333204
 
3.8%
c 333204
 
3.8%
333204
 
3.8%
Other values (7) 2331918
26.9%
ValueCountFrequency (%)
n 30069
11.6%
e 30000
11.5%
i 29940
11.5%
l 19983
 
7.7%
o 19974
 
7.7%
a 19914
 
7.7%
O 10026
 
3.9%
I 10017
 
3.9%
- 10017
 
3.9%
t 10017
 
3.9%
Other values (7) 69819
26.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 8665428
100.0%
ValueCountFrequency (%)
(unknown) 259776
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
n 1000490
11.5%
i 1000102
11.5%
e 1000000
11.5%
l 666898
 
7.7%
a 666408
 
7.7%
o 666306
 
7.7%
O 333694
 
3.9%
S 333204
 
3.8%
c 333204
 
3.8%
333204
 
3.8%
Other values (7) 2331918
26.9%
ValueCountFrequency (%)
n 30069
11.6%
e 30000
11.5%
i 29940
11.5%
l 19983
 
7.7%
o 19974
 
7.7%
a 19914
 
7.7%
O 10026
 
3.9%
I 10017
 
3.9%
- 10017
 
3.9%
t 10017
 
3.9%
Other values (7) 69819
26.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 8665428
100.0%
ValueCountFrequency (%)
(unknown) 259776
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
n 1000490
11.5%
i 1000102
11.5%
e 1000000
11.5%
l 666898
 
7.7%
a 666408
 
7.7%
o 666306
 
7.7%
O 333694
 
3.9%
S 333204
 
3.8%
c 333204
 
3.8%
333204
 
3.8%
Other values (7) 2331918
26.9%
ValueCountFrequency (%)
n 30069
11.6%
e 30000
11.5%
i 29940
11.5%
l 19983
 
7.7%
o 19974
 
7.7%
a 19914
 
7.7%
O 10026
 
3.9%
I 10017
 
3.9%
- 10017
 
3.9%
t 10017
 
3.9%
Other values (7) 69819
26.9%
 Full DatasetSystematic Sample
Distinct22
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T02:08:26.427413image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

 Full DatasetSystematic Sample
Max length1919
Median length1319
Mean length15.99929216.0132
Min length1313

Characters and Unicode

 Full DatasetSystematic Sample
Total characters15999292480396
Distinct characters1515
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Full DatasetSystematic Sample
Unique00 ?
Unique (%)0.0%0.0%

Sample

 Full DatasetSystematic Sample
1st rowNew CustomersNew Customers
2nd rowNew CustomersReturning Customers
3rd rowNew CustomersReturning Customers
4th rowReturning CustomersReturning Customers
5th rowNew CustomersNew Customers
ValueCountFrequency (%)
customers 1000000
50.0%
new 500118
25.0%
returning 499882
25.0%
ValueCountFrequency (%)
customers 30000
50.0%
returning 15066
25.1%
new 14934
24.9%
2025-06-06T02:08:26.924738image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 2000000
12.5%
s 2000000
12.5%
u 1499882
9.4%
r 1499882
9.4%
t 1499882
9.4%
C 1000000
6.3%
1000000
6.3%
o 1000000
6.3%
m 1000000
6.3%
n 999764
 
6.2%
Other values (5) 2499882
15.6%
ValueCountFrequency (%)
e 60000
12.5%
s 60000
12.5%
t 45066
9.4%
r 45066
9.4%
u 45066
9.4%
n 30132
6.3%
30000
 
6.2%
m 30000
 
6.2%
o 30000
 
6.2%
C 30000
 
6.2%
Other values (5) 75066
15.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 15999292
100.0%
ValueCountFrequency (%)
(unknown) 480396
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 2000000
12.5%
s 2000000
12.5%
u 1499882
9.4%
r 1499882
9.4%
t 1499882
9.4%
C 1000000
6.3%
1000000
6.3%
o 1000000
6.3%
m 1000000
6.3%
n 999764
 
6.2%
Other values (5) 2499882
15.6%
ValueCountFrequency (%)
e 60000
12.5%
s 60000
12.5%
t 45066
9.4%
r 45066
9.4%
u 45066
9.4%
n 30132
6.3%
30000
 
6.2%
m 30000
 
6.2%
o 30000
 
6.2%
C 30000
 
6.2%
Other values (5) 75066
15.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 15999292
100.0%
ValueCountFrequency (%)
(unknown) 480396
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 2000000
12.5%
s 2000000
12.5%
u 1499882
9.4%
r 1499882
9.4%
t 1499882
9.4%
C 1000000
6.3%
1000000
6.3%
o 1000000
6.3%
m 1000000
6.3%
n 999764
 
6.2%
Other values (5) 2499882
15.6%
ValueCountFrequency (%)
e 60000
12.5%
s 60000
12.5%
t 45066
9.4%
r 45066
9.4%
u 45066
9.4%
n 30132
6.3%
30000
 
6.2%
m 30000
 
6.2%
o 30000
 
6.2%
C 30000
 
6.2%
Other values (5) 75066
15.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 15999292
100.0%
ValueCountFrequency (%)
(unknown) 480396
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 2000000
12.5%
s 2000000
12.5%
u 1499882
9.4%
r 1499882
9.4%
t 1499882
9.4%
C 1000000
6.3%
1000000
6.3%
o 1000000
6.3%
m 1000000
6.3%
n 999764
 
6.2%
Other values (5) 2499882
15.6%
ValueCountFrequency (%)
e 60000
12.5%
s 60000
12.5%
t 45066
9.4%
r 45066
9.4%
u 45066
9.4%
n 30132
6.3%
30000
 
6.2%
m 30000
 
6.2%
o 30000
 
6.2%
C 30000
 
6.2%
Other values (5) 75066
15.6%

customer_zip_code
Real number (ℝ)

 Full DatasetSystematic Sample
Distinct8999925475
Distinct (%)9.0%84.9%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean54993.6447755064.10053
 Full DatasetSystematic Sample
Minimum1000010010
Maximum9999899997
Zeros00
Zeros (%)0.0%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T02:08:27.211307image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Full DatasetSystematic Sample
Minimum1000010010
5-th percentile1449114558.8
Q132477.7532675.25
median5496654964.5
Q37749377524
95-th percentile9549795528.25
Maximum9999899997
Range8999889987
Interquartile range (IQR)45015.2544848.75

Descriptive statistics

 Full DatasetSystematic Sample
Standard deviation25975.807825916.44864
Coefficient of variation (CV)0.47234199340.4706596201
Kurtosis-1.199859176-1.188946149
Mean54993.6447755064.10053
Median Absolute Deviation (MAD)2250922420.5
Skewness0.000792464580.00166168672
Sum5.499364477 × 10101651923016
Variance674742590.8671662310.2
MonotonicityNot monotonicNot monotonic
2025-06-06T02:08:27.554506image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
41138 27
 
< 0.1%
28225 27
 
< 0.1%
19719 27
 
< 0.1%
25427 27
 
< 0.1%
95120 26
 
< 0.1%
38515 26
 
< 0.1%
54735 26
 
< 0.1%
21109 26
 
< 0.1%
17611 25
 
< 0.1%
82394 25
 
< 0.1%
Other values (89989) 999738
> 99.9%
ValueCountFrequency (%)
85608 5
 
< 0.1%
31400 4
 
< 0.1%
91851 4
 
< 0.1%
46968 4
 
< 0.1%
69565 4
 
< 0.1%
92038 4
 
< 0.1%
35166 4
 
< 0.1%
29928 4
 
< 0.1%
53168 4
 
< 0.1%
13987 4
 
< 0.1%
Other values (25465) 29959
99.9%
ValueCountFrequency (%)
10000 12
< 0.1%
10001 14
< 0.1%
10002 6
< 0.1%
10003 12
< 0.1%
10004 5
 
< 0.1%
ValueCountFrequency (%)
10010 1
< 0.1%
10016 1
< 0.1%
10017 2
< 0.1%
10018 1
< 0.1%
10020 1
< 0.1%
ValueCountFrequency (%)
10010 1
< 0.1%
10016 1
< 0.1%
10017 2
< 0.1%
10018 1
< 0.1%
10020 1
< 0.1%
ValueCountFrequency (%)
10000 12
< 0.1%
10001 14
< 0.1%
10002 6
< 0.1%
10003 12
< 0.1%
10004 5
 
< 0.1%

customer_city
['Text', 'Text']

 Full DatasetSystematic Sample
Distinct44
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T02:08:27.822449image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

 Full DatasetSystematic Sample
Max length66
Median length66
Mean length66
Min length66

Characters and Unicode

 Full DatasetSystematic Sample
Total characters6000000180000
Distinct characters88
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Full DatasetSystematic Sample
Unique00 ?
Unique (%)0.0%0.0%

Sample

 Full DatasetSystematic Sample
1st rowCity DCity D
2nd rowCity ACity D
3rd rowCity BCity C
4th rowCity ACity A
5th rowCity BCity A
ValueCountFrequency (%)
city 1000000
50.0%
b 250788
 
12.5%
c 249955
 
12.5%
a 249698
 
12.5%
d 249559
 
12.5%
ValueCountFrequency (%)
city 30000
50.0%
d 7560
 
12.6%
b 7532
 
12.6%
c 7460
 
12.4%
a 7448
 
12.4%
2025-06-06T02:08:28.194449image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
C 1249955
20.8%
i 1000000
16.7%
t 1000000
16.7%
y 1000000
16.7%
1000000
16.7%
B 250788
 
4.2%
A 249698
 
4.2%
D 249559
 
4.2%
ValueCountFrequency (%)
C 37460
20.8%
i 30000
16.7%
t 30000
16.7%
y 30000
16.7%
30000
16.7%
D 7560
 
4.2%
B 7532
 
4.2%
A 7448
 
4.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 6000000
100.0%
ValueCountFrequency (%)
(unknown) 180000
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
C 1249955
20.8%
i 1000000
16.7%
t 1000000
16.7%
y 1000000
16.7%
1000000
16.7%
B 250788
 
4.2%
A 249698
 
4.2%
D 249559
 
4.2%
ValueCountFrequency (%)
C 37460
20.8%
i 30000
16.7%
t 30000
16.7%
y 30000
16.7%
30000
16.7%
D 7560
 
4.2%
B 7532
 
4.2%
A 7448
 
4.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 6000000
100.0%
ValueCountFrequency (%)
(unknown) 180000
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
C 1249955
20.8%
i 1000000
16.7%
t 1000000
16.7%
y 1000000
16.7%
1000000
16.7%
B 250788
 
4.2%
A 249698
 
4.2%
D 249559
 
4.2%
ValueCountFrequency (%)
C 37460
20.8%
i 30000
16.7%
t 30000
16.7%
y 30000
16.7%
30000
16.7%
D 7560
 
4.2%
B 7532
 
4.2%
A 7448
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 6000000
100.0%
ValueCountFrequency (%)
(unknown) 180000
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
C 1249955
20.8%
i 1000000
16.7%
t 1000000
16.7%
y 1000000
16.7%
1000000
16.7%
B 250788
 
4.2%
A 249698
 
4.2%
D 249559
 
4.2%
ValueCountFrequency (%)
C 37460
20.8%
i 30000
16.7%
t 30000
16.7%
y 30000
16.7%
30000
16.7%
D 7560
 
4.2%
B 7532
 
4.2%
A 7448
 
4.1%

customer_state
['Text', 'Text']

 Full DatasetSystematic Sample
Distinct33
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T02:08:28.431382image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

 Full DatasetSystematic Sample
Max length77
Median length77
Mean length77
Min length77

Characters and Unicode

 Full DatasetSystematic Sample
Total characters7000000210000
Distinct characters88
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Full DatasetSystematic Sample
Unique00 ?
Unique (%)0.0%0.0%

Sample

 Full DatasetSystematic Sample
1st rowState YState Y
2nd rowState XState X
3rd rowState XState X
4th rowState YState X
5th rowState ZState X
ValueCountFrequency (%)
state 1000000
50.0%
z 333674
 
16.7%
x 333196
 
16.7%
y 333130
 
16.7%
ValueCountFrequency (%)
state 30000
50.0%
z 10166
 
16.9%
x 9984
 
16.6%
y 9850
 
16.4%
2025-06-06T02:08:28.817151image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 2000000
28.6%
S 1000000
14.3%
a 1000000
14.3%
e 1000000
14.3%
1000000
14.3%
Z 333674
 
4.8%
X 333196
 
4.8%
Y 333130
 
4.8%
ValueCountFrequency (%)
t 60000
28.6%
S 30000
14.3%
a 30000
14.3%
e 30000
14.3%
30000
14.3%
Z 10166
 
4.8%
X 9984
 
4.8%
Y 9850
 
4.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 7000000
100.0%
ValueCountFrequency (%)
(unknown) 210000
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
t 2000000
28.6%
S 1000000
14.3%
a 1000000
14.3%
e 1000000
14.3%
1000000
14.3%
Z 333674
 
4.8%
X 333196
 
4.8%
Y 333130
 
4.8%
ValueCountFrequency (%)
t 60000
28.6%
S 30000
14.3%
a 30000
14.3%
e 30000
14.3%
30000
14.3%
Z 10166
 
4.8%
X 9984
 
4.8%
Y 9850
 
4.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 7000000
100.0%
ValueCountFrequency (%)
(unknown) 210000
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
t 2000000
28.6%
S 1000000
14.3%
a 1000000
14.3%
e 1000000
14.3%
1000000
14.3%
Z 333674
 
4.8%
X 333196
 
4.8%
Y 333130
 
4.8%
ValueCountFrequency (%)
t 60000
28.6%
S 30000
14.3%
a 30000
14.3%
e 30000
14.3%
30000
14.3%
Z 10166
 
4.8%
X 9984
 
4.8%
Y 9850
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 7000000
100.0%
ValueCountFrequency (%)
(unknown) 210000
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
t 2000000
28.6%
S 1000000
14.3%
a 1000000
14.3%
e 1000000
14.3%
1000000
14.3%
Z 333674
 
4.8%
X 333196
 
4.8%
Y 333130
 
4.8%
ValueCountFrequency (%)
t 60000
28.6%
S 30000
14.3%
a 30000
14.3%
e 30000
14.3%
30000
14.3%
Z 10166
 
4.8%
X 9984
 
4.8%
Y 9850
 
4.7%

store_zip_code
Real number (ℝ)

 Full DatasetSystematic Sample
Distinct8999925596
Distinct (%)9.0%85.3%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean54972.7667155034.19067
 Full DatasetSystematic Sample
Minimum1000010002
Maximum9999899986
Zeros00
Zeros (%)0.0%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T02:08:29.081937image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Full DatasetSystematic Sample
Minimum1000010002
5-th percentile1448814519.8
Q13247332677
median5496155112
Q37745177636.5
95-th percentile9547095479.05
Maximum9999899986
Range8999889984
Interquartile range (IQR)4497844959.5

Descriptive statistics

 Full DatasetSystematic Sample
Standard deviation25981.4831425923.60613
Coefficient of variation (CV)0.47262462290.4710454686
Kurtosis-1.200166165-1.19592475
Mean54972.7667155034.19067
Median Absolute Deviation (MAD)22489.522474.5
Skewness-0.00010396262037.98280138 × 10-5
Sum5.497276671 × 10101651025720
Variance675037466.1672033354.9
MonotonicityNot monotonicNot monotonic
2025-06-06T02:08:29.460262image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20956 28
 
< 0.1%
29159 27
 
< 0.1%
59836 26
 
< 0.1%
54696 26
 
< 0.1%
92910 26
 
< 0.1%
43369 26
 
< 0.1%
26386 26
 
< 0.1%
90024 26
 
< 0.1%
27134 26
 
< 0.1%
20477 26
 
< 0.1%
Other values (89989) 999737
> 99.9%
ValueCountFrequency (%)
68167 5
 
< 0.1%
60742 5
 
< 0.1%
38394 4
 
< 0.1%
55278 4
 
< 0.1%
36335 4
 
< 0.1%
13347 4
 
< 0.1%
90174 4
 
< 0.1%
38593 4
 
< 0.1%
88114 4
 
< 0.1%
57024 4
 
< 0.1%
Other values (25586) 29958
99.9%
ValueCountFrequency (%)
10000 11
< 0.1%
10001 6
 
< 0.1%
10002 15
< 0.1%
10003 8
< 0.1%
10004 14
< 0.1%
ValueCountFrequency (%)
10002 1
 
< 0.1%
10012 1
 
< 0.1%
10013 3
< 0.1%
10014 2
< 0.1%
10016 1
 
< 0.1%
ValueCountFrequency (%)
10002 1
 
< 0.1%
10012 1
 
< 0.1%
10013 3
< 0.1%
10014 2
< 0.1%
10016 1
 
< 0.1%
ValueCountFrequency (%)
10000 11
< 0.1%
10001 6
 
< 0.1%
10002 15
0.1%
10003 8
< 0.1%
10004 14
< 0.1%

store_city
['Text', 'Text']

 Full DatasetSystematic Sample
Distinct44
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T02:08:29.786237image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

 Full DatasetSystematic Sample
Max length66
Median length66
Mean length66
Min length66

Characters and Unicode

 Full DatasetSystematic Sample
Total characters6000000180000
Distinct characters88
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Full DatasetSystematic Sample
Unique00 ?
Unique (%)0.0%0.0%

Sample

 Full DatasetSystematic Sample
1st rowCity DCity D
2nd rowCity CCity B
3rd rowCity ACity D
4th rowCity BCity C
5th rowCity CCity D
ValueCountFrequency (%)
city 1000000
50.0%
d 250315
 
12.5%
c 250177
 
12.5%
b 249965
 
12.5%
a 249543
 
12.5%
ValueCountFrequency (%)
city 30000
50.0%
d 7593
 
12.7%
b 7546
 
12.6%
a 7462
 
12.4%
c 7399
 
12.3%
2025-06-06T02:08:30.028078image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
C 1250177
20.8%
i 1000000
16.7%
t 1000000
16.7%
y 1000000
16.7%
1000000
16.7%
D 250315
 
4.2%
B 249965
 
4.2%
A 249543
 
4.2%
ValueCountFrequency (%)
C 37399
20.8%
i 30000
16.7%
t 30000
16.7%
y 30000
16.7%
30000
16.7%
D 7593
 
4.2%
B 7546
 
4.2%
A 7462
 
4.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 6000000
100.0%
ValueCountFrequency (%)
(unknown) 180000
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
C 1250177
20.8%
i 1000000
16.7%
t 1000000
16.7%
y 1000000
16.7%
1000000
16.7%
D 250315
 
4.2%
B 249965
 
4.2%
A 249543
 
4.2%
ValueCountFrequency (%)
C 37399
20.8%
i 30000
16.7%
t 30000
16.7%
y 30000
16.7%
30000
16.7%
D 7593
 
4.2%
B 7546
 
4.2%
A 7462
 
4.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 6000000
100.0%
ValueCountFrequency (%)
(unknown) 180000
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
C 1250177
20.8%
i 1000000
16.7%
t 1000000
16.7%
y 1000000
16.7%
1000000
16.7%
D 250315
 
4.2%
B 249965
 
4.2%
A 249543
 
4.2%
ValueCountFrequency (%)
C 37399
20.8%
i 30000
16.7%
t 30000
16.7%
y 30000
16.7%
30000
16.7%
D 7593
 
4.2%
B 7546
 
4.2%
A 7462
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 6000000
100.0%
ValueCountFrequency (%)
(unknown) 180000
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
C 1250177
20.8%
i 1000000
16.7%
t 1000000
16.7%
y 1000000
16.7%
1000000
16.7%
D 250315
 
4.2%
B 249965
 
4.2%
A 249543
 
4.2%
ValueCountFrequency (%)
C 37399
20.8%
i 30000
16.7%
t 30000
16.7%
y 30000
16.7%
30000
16.7%
D 7593
 
4.2%
B 7546
 
4.2%
A 7462
 
4.1%

store_state
['Text', 'Text']

 Full DatasetSystematic Sample
Distinct33
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T02:08:30.215595image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

 Full DatasetSystematic Sample
Max length77
Median length77
Mean length77
Min length77

Characters and Unicode

 Full DatasetSystematic Sample
Total characters7000000210000
Distinct characters88
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Full DatasetSystematic Sample
Unique00 ?
Unique (%)0.0%0.0%

Sample

 Full DatasetSystematic Sample
1st rowState YState Y
2nd rowState XState Y
3rd rowState YState X
4th rowState ZState Y
5th rowState XState Z
ValueCountFrequency (%)
state 1000000
50.0%
x 333702
 
16.7%
z 333602
 
16.7%
y 332696
 
16.6%
ValueCountFrequency (%)
state 30000
50.0%
x 10054
 
16.8%
y 10012
 
16.7%
z 9934
 
16.6%
2025-06-06T02:08:30.481157image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 2000000
28.6%
S 1000000
14.3%
a 1000000
14.3%
e 1000000
14.3%
1000000
14.3%
X 333702
 
4.8%
Z 333602
 
4.8%
Y 332696
 
4.8%
ValueCountFrequency (%)
t 60000
28.6%
S 30000
14.3%
a 30000
14.3%
e 30000
14.3%
30000
14.3%
X 10054
 
4.8%
Y 10012
 
4.8%
Z 9934
 
4.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 7000000
100.0%
ValueCountFrequency (%)
(unknown) 210000
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
t 2000000
28.6%
S 1000000
14.3%
a 1000000
14.3%
e 1000000
14.3%
1000000
14.3%
X 333702
 
4.8%
Z 333602
 
4.8%
Y 332696
 
4.8%
ValueCountFrequency (%)
t 60000
28.6%
S 30000
14.3%
a 30000
14.3%
e 30000
14.3%
30000
14.3%
X 10054
 
4.8%
Y 10012
 
4.8%
Z 9934
 
4.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 7000000
100.0%
ValueCountFrequency (%)
(unknown) 210000
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
t 2000000
28.6%
S 1000000
14.3%
a 1000000
14.3%
e 1000000
14.3%
1000000
14.3%
X 333702
 
4.8%
Z 333602
 
4.8%
Y 332696
 
4.8%
ValueCountFrequency (%)
t 60000
28.6%
S 30000
14.3%
a 30000
14.3%
e 30000
14.3%
30000
14.3%
X 10054
 
4.8%
Y 10012
 
4.8%
Z 9934
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 7000000
100.0%
ValueCountFrequency (%)
(unknown) 210000
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
t 2000000
28.6%
S 1000000
14.3%
a 1000000
14.3%
e 1000000
14.3%
1000000
14.3%
X 333702
 
4.8%
Z 333602
 
4.8%
Y 332696
 
4.8%
ValueCountFrequency (%)
t 60000
28.6%
S 30000
14.3%
a 30000
14.3%
e 30000
14.3%
30000
14.3%
X 10054
 
4.8%
Y 10012
 
4.8%
Z 9934
 
4.7%

distance_to_store
Real number (ℝ)

 Full DatasetSystematic Sample
Distinct100019500
Distinct (%)1.0%31.7%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean49.9791092449.98382167
 Full DatasetSystematic Sample
Minimum00
Maximum100100
Zeros623
Zeros (%)< 0.1%< 0.1%
Negative00
Negative (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T02:08:30.643140image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Full DatasetSystematic Sample
Minimum00
5-th percentile5.035.14
Q124.9724.9075
median49.9649.99
Q374.9574.98
95-th percentile94.9895.0305
Maximum100100
Range100100
Interquartile range (IQR)49.9850.0725

Descriptive statistics

 Full DatasetSystematic Sample
Standard deviation28.8609891128.84972589
Coefficient of variation (CV)0.57746105430.5771812744
Kurtosis-1.200199633-1.199578709
Mean49.9791092449.98382167
Median Absolute Deviation (MAD)24.9925.025
Skewness0.0012182864680.004047268387
Sum49979109.241499514.65
Variance832.9566927832.3066839
MonotonicityNot monotonicNot monotonic
2025-06-06T02:08:30.856970image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
99.05 139
 
< 0.1%
0.01 138
 
< 0.1%
9.68 138
 
< 0.1%
30.79 136
 
< 0.1%
31.27 135
 
< 0.1%
22.61 134
 
< 0.1%
40.84 134
 
< 0.1%
78.41 134
 
< 0.1%
82.37 133
 
< 0.1%
89.9 133
 
< 0.1%
Other values (9991) 998646
99.9%
ValueCountFrequency (%)
63.94 12
 
< 0.1%
10.03 10
 
< 0.1%
21.8 10
 
< 0.1%
86.61 10
 
< 0.1%
87.5 10
 
< 0.1%
26.41 10
 
< 0.1%
61.87 10
 
< 0.1%
73.07 9
 
< 0.1%
44.38 9
 
< 0.1%
39.03 9
 
< 0.1%
Other values (9490) 29901
99.7%
ValueCountFrequency (%)
0 62
< 0.1%
0.01 138
< 0.1%
0.02 88
< 0.1%
0.03 113
< 0.1%
0.04 86
< 0.1%
ValueCountFrequency (%)
0 3
< 0.1%
0.01 5
< 0.1%
0.02 1
 
< 0.1%
0.03 2
 
< 0.1%
0.04 2
 
< 0.1%
ValueCountFrequency (%)
0 3
< 0.1%
0.01 5
< 0.1%
0.02 1
 
< 0.1%
0.03 2
 
< 0.1%
0.04 2
 
< 0.1%
ValueCountFrequency (%)
0 62
0.2%
0.01 138
0.5%
0.02 88
0.3%
0.03 113
0.4%
0.04 86
0.3%

holiday_season
['Text', 'Text']

 Full DatasetSystematic Sample
Distinct22
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T02:08:31.045399image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

 Full DatasetSystematic Sample
Max length33
Median length33
Mean length2.5002142.505
Min length22

Characters and Unicode

 Full DatasetSystematic Sample
Total characters250021475150
Distinct characters55
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Full DatasetSystematic Sample
Unique00 ?
Unique (%)0.0%0.0%

Sample

 Full DatasetSystematic Sample
1st rowNoNo
2nd rowNoNo
3rd rowYesNo
4th rowYesNo
5th rowYesNo
ValueCountFrequency (%)
yes 500214
50.0%
no 499786
50.0%
ValueCountFrequency (%)
yes 15150
50.5%
no 14850
49.5%
2025-06-06T02:08:31.323681image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
Y 500214
20.0%
e 500214
20.0%
s 500214
20.0%
N 499786
20.0%
o 499786
20.0%
ValueCountFrequency (%)
Y 15150
20.2%
e 15150
20.2%
s 15150
20.2%
N 14850
19.8%
o 14850
19.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2500214
100.0%
ValueCountFrequency (%)
(unknown) 75150
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
Y 500214
20.0%
e 500214
20.0%
s 500214
20.0%
N 499786
20.0%
o 499786
20.0%
ValueCountFrequency (%)
Y 15150
20.2%
e 15150
20.2%
s 15150
20.2%
N 14850
19.8%
o 14850
19.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2500214
100.0%
ValueCountFrequency (%)
(unknown) 75150
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
Y 500214
20.0%
e 500214
20.0%
s 500214
20.0%
N 499786
20.0%
o 499786
20.0%
ValueCountFrequency (%)
Y 15150
20.2%
e 15150
20.2%
s 15150
20.2%
N 14850
19.8%
o 14850
19.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2500214
100.0%
ValueCountFrequency (%)
(unknown) 75150
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
Y 500214
20.0%
e 500214
20.0%
s 500214
20.0%
N 499786
20.0%
o 499786
20.0%
ValueCountFrequency (%)
Y 15150
20.2%
e 15150
20.2%
s 15150
20.2%
N 14850
19.8%
o 14850
19.8%

season
['Text', 'Text']

 Full DatasetSystematic Sample
Distinct44
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T02:08:31.543832image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

 Full DatasetSystematic Sample
Max length66
Median length66
Mean length5.5003225.493333333
Min length44

Characters and Unicode

 Full DatasetSystematic Sample
Total characters5500322164800
Distinct characters1414
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Full DatasetSystematic Sample
Unique00 ?
Unique (%)0.0%0.0%

Sample

 Full DatasetSystematic Sample
1st rowSpringSpring
2nd rowSummerSpring
3rd rowWinterSpring
4th rowWinterWinter
5th rowSummerFall
ValueCountFrequency (%)
winter 250307
25.0%
spring 250169
25.0%
fall 249839
25.0%
summer 249685
25.0%
ValueCountFrequency (%)
fall 7600
25.3%
winter 7519
25.1%
spring 7492
25.0%
summer 7389
24.6%
2025-06-06T02:08:31.916860image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
r 750161
13.6%
i 500476
9.1%
n 500476
9.1%
e 499992
9.1%
S 499854
9.1%
l 499678
9.1%
m 499370
9.1%
W 250307
 
4.6%
t 250307
 
4.6%
p 250169
 
4.5%
Other values (4) 999532
18.2%
ValueCountFrequency (%)
r 22400
13.6%
l 15200
9.2%
n 15011
9.1%
i 15011
9.1%
e 14908
9.0%
S 14881
9.0%
m 14778
9.0%
F 7600
 
4.6%
a 7600
 
4.6%
W 7519
 
4.6%
Other values (4) 29892
18.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 5500322
100.0%
ValueCountFrequency (%)
(unknown) 164800
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
r 750161
13.6%
i 500476
9.1%
n 500476
9.1%
e 499992
9.1%
S 499854
9.1%
l 499678
9.1%
m 499370
9.1%
W 250307
 
4.6%
t 250307
 
4.6%
p 250169
 
4.5%
Other values (4) 999532
18.2%
ValueCountFrequency (%)
r 22400
13.6%
l 15200
9.2%
n 15011
9.1%
i 15011
9.1%
e 14908
9.0%
S 14881
9.0%
m 14778
9.0%
F 7600
 
4.6%
a 7600
 
4.6%
W 7519
 
4.6%
Other values (4) 29892
18.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 5500322
100.0%
ValueCountFrequency (%)
(unknown) 164800
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
r 750161
13.6%
i 500476
9.1%
n 500476
9.1%
e 499992
9.1%
S 499854
9.1%
l 499678
9.1%
m 499370
9.1%
W 250307
 
4.6%
t 250307
 
4.6%
p 250169
 
4.5%
Other values (4) 999532
18.2%
ValueCountFrequency (%)
r 22400
13.6%
l 15200
9.2%
n 15011
9.1%
i 15011
9.1%
e 14908
9.0%
S 14881
9.0%
m 14778
9.0%
F 7600
 
4.6%
a 7600
 
4.6%
W 7519
 
4.6%
Other values (4) 29892
18.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 5500322
100.0%
ValueCountFrequency (%)
(unknown) 164800
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
r 750161
13.6%
i 500476
9.1%
n 500476
9.1%
e 499992
9.1%
S 499854
9.1%
l 499678
9.1%
m 499370
9.1%
W 250307
 
4.6%
t 250307
 
4.6%
p 250169
 
4.5%
Other values (4) 999532
18.2%
ValueCountFrequency (%)
r 22400
13.6%
l 15200
9.2%
n 15011
9.1%
i 15011
9.1%
e 14908
9.0%
S 14881
9.0%
m 14778
9.0%
F 7600
 
4.6%
a 7600
 
4.6%
W 7519
 
4.6%
Other values (4) 29892
18.1%

weekend
['Text', 'Text']

 Full DatasetSystematic Sample
Distinct22
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T02:08:32.067818image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

 Full DatasetSystematic Sample
Max length33
Median length23
Mean length2.4993332.500333333
Min length22

Characters and Unicode

 Full DatasetSystematic Sample
Total characters249933375010
Distinct characters55
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Full DatasetSystematic Sample
Unique00 ?
Unique (%)0.0%0.0%

Sample

 Full DatasetSystematic Sample
1st rowYesYes
2nd rowYesYes
3rd rowYesYes
4th rowNoNo
5th rowYesNo
ValueCountFrequency (%)
no 500667
50.1%
yes 499333
49.9%
ValueCountFrequency (%)
yes 15010
50.0%
no 14990
50.0%
2025-06-06T02:08:32.335182image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 500667
20.0%
o 500667
20.0%
Y 499333
20.0%
e 499333
20.0%
s 499333
20.0%
ValueCountFrequency (%)
Y 15010
20.0%
e 15010
20.0%
s 15010
20.0%
N 14990
20.0%
o 14990
20.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2499333
100.0%
ValueCountFrequency (%)
(unknown) 75010
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
N 500667
20.0%
o 500667
20.0%
Y 499333
20.0%
e 499333
20.0%
s 499333
20.0%
ValueCountFrequency (%)
Y 15010
20.0%
e 15010
20.0%
s 15010
20.0%
N 14990
20.0%
o 14990
20.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2499333
100.0%
ValueCountFrequency (%)
(unknown) 75010
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
N 500667
20.0%
o 500667
20.0%
Y 499333
20.0%
e 499333
20.0%
s 499333
20.0%
ValueCountFrequency (%)
Y 15010
20.0%
e 15010
20.0%
s 15010
20.0%
N 14990
20.0%
o 14990
20.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2499333
100.0%
ValueCountFrequency (%)
(unknown) 75010
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
N 500667
20.0%
o 500667
20.0%
Y 499333
20.0%
e 499333
20.0%
s 499333
20.0%
ValueCountFrequency (%)
Y 15010
20.0%
e 15010
20.0%
s 15010
20.0%
N 14990
20.0%
o 14990
20.0%

customer_support_calls
Real number (ℝ)

 Full DatasetSystematic Sample
Distinct2020
Distinct (%)< 0.1%0.1%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean9.4962699.496366667
 Full DatasetSystematic Sample
Minimum00
Maximum1919
Zeros497551560
Zeros (%)5.0%5.2%
Negative00
Negative (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T02:08:32.448641image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Full DatasetSystematic Sample
Minimum00
5-th percentile10
Q144
median910
Q31415
95-th percentile1818
Maximum1919
Range1919
Interquartile range (IQR)1011

Descriptive statistics

 Full DatasetSystematic Sample
Standard deviation5.7612327915.790587578
Coefficient of variation (CV)0.6066838240.6097687443
Kurtosis-1.204539564-1.215817005
Mean9.4962699.496366667
Median Absolute Deviation (MAD)55
Skewness0.001572025506-0.004931043499
Sum9496269284891
Variance33.1918032733.5309045
MonotonicityNot monotonicNot monotonic
2025-06-06T02:08:32.577325image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
3 50608
 
5.1%
8 50350
 
5.0%
4 50334
 
5.0%
12 50312
 
5.0%
2 50158
 
5.0%
11 50151
 
5.0%
16 50087
 
5.0%
13 50074
 
5.0%
9 50053
 
5.0%
7 50050
 
5.0%
Other values (10) 497823
49.8%
ValueCountFrequency (%)
13 1567
 
5.2%
0 1560
 
5.2%
11 1558
 
5.2%
8 1556
 
5.2%
16 1551
 
5.2%
17 1547
 
5.2%
1 1536
 
5.1%
5 1531
 
5.1%
3 1519
 
5.1%
18 1515
 
5.1%
Other values (10) 14560
48.5%
ValueCountFrequency (%)
0 49755
5.0%
1 49530
5.0%
2 50158
5.0%
3 50608
5.1%
4 50334
5.0%
ValueCountFrequency (%)
0 1560
5.2%
1 1536
5.1%
2 1456
4.9%
3 1519
5.1%
4 1485
5.0%
ValueCountFrequency (%)
0 1560
0.2%
1 1536
0.2%
2 1456
0.1%
3 1519
0.2%
4 1485
0.1%
ValueCountFrequency (%)
0 49755
165.9%
1 49530
165.1%
2 50158
167.2%
3 50608
168.7%
4 50334
167.8%

email_subscriptions
['Text', 'Text']

 Full DatasetSystematic Sample
Distinct22
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T02:08:32.764977image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

 Full DatasetSystematic Sample
Max length33
Median length23
Mean length2.4999382.501266667
Min length22

Characters and Unicode

 Full DatasetSystematic Sample
Total characters249993875038
Distinct characters55
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Full DatasetSystematic Sample
Unique00 ?
Unique (%)0.0%0.0%

Sample

 Full DatasetSystematic Sample
1st rowNoNo
2nd rowNoNo
3rd rowYesYes
4th rowNoNo
5th rowNoNo
ValueCountFrequency (%)
no 500062
50.0%
yes 499938
50.0%
ValueCountFrequency (%)
yes 15038
50.1%
no 14962
49.9%
2025-06-06T02:08:33.039499image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 500062
20.0%
o 500062
20.0%
Y 499938
20.0%
e 499938
20.0%
s 499938
20.0%
ValueCountFrequency (%)
Y 15038
20.0%
e 15038
20.0%
s 15038
20.0%
N 14962
19.9%
o 14962
19.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2499938
100.0%
ValueCountFrequency (%)
(unknown) 75038
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
N 500062
20.0%
o 500062
20.0%
Y 499938
20.0%
e 499938
20.0%
s 499938
20.0%
ValueCountFrequency (%)
Y 15038
20.0%
e 15038
20.0%
s 15038
20.0%
N 14962
19.9%
o 14962
19.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2499938
100.0%
ValueCountFrequency (%)
(unknown) 75038
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
N 500062
20.0%
o 500062
20.0%
Y 499938
20.0%
e 499938
20.0%
s 499938
20.0%
ValueCountFrequency (%)
Y 15038
20.0%
e 15038
20.0%
s 15038
20.0%
N 14962
19.9%
o 14962
19.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2499938
100.0%
ValueCountFrequency (%)
(unknown) 75038
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
N 500062
20.0%
o 500062
20.0%
Y 499938
20.0%
e 499938
20.0%
s 499938
20.0%
ValueCountFrequency (%)
Y 15038
20.0%
e 15038
20.0%
s 15038
20.0%
N 14962
19.9%
o 14962
19.9%

app_usage
['Text', 'Text']

 Full DatasetSystematic Sample
Distinct33
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T02:08:33.236778image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

 Full DatasetSystematic Sample
Max length66
Median length44
Mean length4.3342994.3313
Min length33

Characters and Unicode

 Full DatasetSystematic Sample
Total characters4334299129939
Distinct characters1212
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Full DatasetSystematic Sample
Unique00 ?
Unique (%)0.0%0.0%

Sample

 Full DatasetSystematic Sample
1st rowHighHigh
2nd rowHighLow
3rd rowLowMedium
4th rowLowLow
5th rowMediumMedium
ValueCountFrequency (%)
medium 333822
33.4%
low 333345
33.3%
high 332833
33.3%
ValueCountFrequency (%)
low 10131
33.8%
medium 10035
33.5%
high 9834
32.8%
2025-06-06T02:08:33.570745image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i 666655
15.4%
M 333822
7.7%
e 333822
7.7%
d 333822
7.7%
u 333822
7.7%
m 333822
7.7%
L 333345
7.7%
o 333345
7.7%
w 333345
7.7%
H 332833
7.7%
Other values (2) 665666
15.4%
ValueCountFrequency (%)
i 19869
15.3%
L 10131
7.8%
w 10131
7.8%
o 10131
7.8%
M 10035
7.7%
e 10035
7.7%
d 10035
7.7%
u 10035
7.7%
m 10035
7.7%
H 9834
7.6%
Other values (2) 19668
15.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4334299
100.0%
ValueCountFrequency (%)
(unknown) 129939
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
i 666655
15.4%
M 333822
7.7%
e 333822
7.7%
d 333822
7.7%
u 333822
7.7%
m 333822
7.7%
L 333345
7.7%
o 333345
7.7%
w 333345
7.7%
H 332833
7.7%
Other values (2) 665666
15.4%
ValueCountFrequency (%)
i 19869
15.3%
L 10131
7.8%
w 10131
7.8%
o 10131
7.8%
M 10035
7.7%
e 10035
7.7%
d 10035
7.7%
u 10035
7.7%
m 10035
7.7%
H 9834
7.6%
Other values (2) 19668
15.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4334299
100.0%
ValueCountFrequency (%)
(unknown) 129939
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
i 666655
15.4%
M 333822
7.7%
e 333822
7.7%
d 333822
7.7%
u 333822
7.7%
m 333822
7.7%
L 333345
7.7%
o 333345
7.7%
w 333345
7.7%
H 332833
7.7%
Other values (2) 665666
15.4%
ValueCountFrequency (%)
i 19869
15.3%
L 10131
7.8%
w 10131
7.8%
o 10131
7.8%
M 10035
7.7%
e 10035
7.7%
d 10035
7.7%
u 10035
7.7%
m 10035
7.7%
H 9834
7.6%
Other values (2) 19668
15.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4334299
100.0%
ValueCountFrequency (%)
(unknown) 129939
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
i 666655
15.4%
M 333822
7.7%
e 333822
7.7%
d 333822
7.7%
u 333822
7.7%
m 333822
7.7%
L 333345
7.7%
o 333345
7.7%
w 333345
7.7%
H 332833
7.7%
Other values (2) 665666
15.4%
ValueCountFrequency (%)
i 19869
15.3%
L 10131
7.8%
w 10131
7.8%
o 10131
7.8%
M 10035
7.7%
e 10035
7.7%
d 10035
7.7%
u 10035
7.7%
m 10035
7.7%
H 9834
7.6%
Other values (2) 19668
15.1%

website_visits
Real number (ℝ)

 Full DatasetSystematic Sample
Distinct100100
Distinct (%)< 0.1%0.3%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean49.51295149.32383333
 Full DatasetSystematic Sample
Minimum00
Maximum9999
Zeros10111296
Zeros (%)1.0%1.0%
Negative00
Negative (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T02:08:33.735039image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Full DatasetSystematic Sample
Minimum00
5-th percentile45
Q12524
median5049
Q37574
95-th percentile9594
Maximum9999
Range9999
Interquartile range (IQR)5050

Descriptive statistics

 Full DatasetSystematic Sample
Standard deviation28.8697769928.83333737
Coefficient of variation (CV)0.58307526440.584572111
Kurtosis-1.199464505-1.200055603
Mean49.51295149.32383333
Median Absolute Deviation (MAD)2525
Skewness-0.00063068125760.008063985979
Sum495129511479715
Variance833.4640237831.361344
MonotonicityNot monotonicNot monotonic
2025-06-06T02:08:33.946405image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
58 10304
 
1.0%
95 10250
 
1.0%
50 10235
 
1.0%
62 10177
 
1.0%
45 10175
 
1.0%
13 10166
 
1.0%
38 10160
 
1.0%
84 10147
 
1.0%
98 10136
 
1.0%
93 10132
 
1.0%
Other values (90) 898118
89.8%
ValueCountFrequency (%)
25 338
 
1.1%
5 337
 
1.1%
53 335
 
1.1%
12 332
 
1.1%
85 331
 
1.1%
46 330
 
1.1%
44 328
 
1.1%
8 324
 
1.1%
76 324
 
1.1%
4 323
 
1.1%
Other values (90) 26698
89.0%
ValueCountFrequency (%)
0 10111
1.0%
1 9997
1.0%
2 9933
1.0%
3 10007
1.0%
4 9969
1.0%
ValueCountFrequency (%)
0 296
1.0%
1 274
0.9%
2 276
0.9%
3 304
1.0%
4 323
1.1%
ValueCountFrequency (%)
0 296
< 0.1%
1 274
< 0.1%
2 276
< 0.1%
3 304
< 0.1%
4 323
< 0.1%
ValueCountFrequency (%)
0 10111
33.7%
1 9997
33.3%
2 9933
33.1%
3 10007
33.4%
4 9969
33.2%

social_media_engagement
['Text', 'Text']

 Full DatasetSystematic Sample
Distinct33
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T02:08:34.184456image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

 Full DatasetSystematic Sample
Max length66
Median length44
Mean length4.3320574.343133333
Min length33

Characters and Unicode

 Full DatasetSystematic Sample
Total characters4332057130294
Distinct characters1212
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Full DatasetSystematic Sample
Unique00 ?
Unique (%)0.0%0.0%

Sample

 Full DatasetSystematic Sample
1st rowHighHigh
2nd rowMediumHigh
3rd rowMediumLow
4th rowLowLow
5th rowLowMedium
ValueCountFrequency (%)
low 334073
33.4%
medium 333065
33.3%
high 332862
33.3%
ValueCountFrequency (%)
medium 10128
33.8%
low 9962
33.2%
high 9910
33.0%
2025-06-06T02:08:34.500748image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i 665927
15.4%
L 334073
7.7%
w 334073
7.7%
o 334073
7.7%
M 333065
7.7%
e 333065
7.7%
d 333065
7.7%
u 333065
7.7%
m 333065
7.7%
H 332862
7.7%
Other values (2) 665724
15.4%
ValueCountFrequency (%)
i 20038
15.4%
M 10128
7.8%
e 10128
7.8%
d 10128
7.8%
u 10128
7.8%
m 10128
7.8%
L 9962
7.6%
o 9962
7.6%
w 9962
7.6%
H 9910
7.6%
Other values (2) 19820
15.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4332057
100.0%
ValueCountFrequency (%)
(unknown) 130294
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
i 665927
15.4%
L 334073
7.7%
w 334073
7.7%
o 334073
7.7%
M 333065
7.7%
e 333065
7.7%
d 333065
7.7%
u 333065
7.7%
m 333065
7.7%
H 332862
7.7%
Other values (2) 665724
15.4%
ValueCountFrequency (%)
i 20038
15.4%
M 10128
7.8%
e 10128
7.8%
d 10128
7.8%
u 10128
7.8%
m 10128
7.8%
L 9962
7.6%
o 9962
7.6%
w 9962
7.6%
H 9910
7.6%
Other values (2) 19820
15.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4332057
100.0%
ValueCountFrequency (%)
(unknown) 130294
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
i 665927
15.4%
L 334073
7.7%
w 334073
7.7%
o 334073
7.7%
M 333065
7.7%
e 333065
7.7%
d 333065
7.7%
u 333065
7.7%
m 333065
7.7%
H 332862
7.7%
Other values (2) 665724
15.4%
ValueCountFrequency (%)
i 20038
15.4%
M 10128
7.8%
e 10128
7.8%
d 10128
7.8%
u 10128
7.8%
m 10128
7.8%
L 9962
7.6%
o 9962
7.6%
w 9962
7.6%
H 9910
7.6%
Other values (2) 19820
15.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4332057
100.0%
ValueCountFrequency (%)
(unknown) 130294
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
i 665927
15.4%
L 334073
7.7%
w 334073
7.7%
o 334073
7.7%
M 333065
7.7%
e 333065
7.7%
d 333065
7.7%
u 333065
7.7%
m 333065
7.7%
H 332862
7.7%
Other values (2) 665724
15.4%
ValueCountFrequency (%)
i 20038
15.4%
M 10128
7.8%
e 10128
7.8%
d 10128
7.8%
u 10128
7.8%
m 10128
7.8%
L 9962
7.6%
o 9962
7.6%
w 9962
7.6%
H 9910
7.6%
Other values (2) 19820
15.2%

days_since_last_purchase
Real number (ℝ)

 Full DatasetSystematic Sample
Distinct365365
Distinct (%)< 0.1%1.2%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean182.027559181.6553333
 Full DatasetSystematic Sample
Minimum00
Maximum364364
Zeros276898
Zeros (%)0.3%0.3%
Negative00
Negative (%)0.0%0.0%
Memory size7.6 MiB234.5 KiB
2025-06-06T02:08:34.668364image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Full DatasetSystematic Sample
Minimum00
5-th percentile1818
Q19191
median182181
Q3273273
95-th percentile346346
Maximum364364
Range364364
Interquartile range (IQR)182182

Descriptive statistics

 Full DatasetSystematic Sample
Standard deviation105.3645979105.2680916
Coefficient of variation (CV)0.57883871230.5794935371
Kurtosis-1.199912738-1.197007882
Mean182.027559181.6553333
Median Absolute Deviation (MAD)9191
Skewness-0.00055431320910.005172950866
Sum1820275595449660
Variance11101.6984811081.37112
MonotonicityNot monotonicNot monotonic
2025-06-06T02:08:34.882414image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
53 2916
 
0.3%
72 2890
 
0.3%
98 2888
 
0.3%
252 2869
 
0.3%
364 2867
 
0.3%
6 2862
 
0.3%
325 2857
 
0.3%
136 2843
 
0.3%
267 2833
 
0.3%
239 2832
 
0.3%
Other values (355) 971343
97.1%
ValueCountFrequency (%)
180 110
 
0.4%
46 110
 
0.4%
147 107
 
0.4%
224 105
 
0.4%
75 105
 
0.4%
32 104
 
0.3%
293 103
 
0.3%
299 102
 
0.3%
266 102
 
0.3%
308 101
 
0.3%
Other values (355) 28951
96.5%
ValueCountFrequency (%)
0 2768
0.3%
1 2752
0.3%
2 2701
0.3%
3 2709
0.3%
4 2786
0.3%
ValueCountFrequency (%)
0 98
0.3%
1 86
0.3%
2 88
0.3%
3 83
0.3%
4 69
0.2%
ValueCountFrequency (%)
0 98
< 0.1%
1 86
< 0.1%
2 88
< 0.1%
3 83
< 0.1%
4 69
< 0.1%
ValueCountFrequency (%)
0 2768
9.2%
1 2752
9.2%
2 2701
9.0%
3 2709
9.0%
4 2786
9.3%